Dear Ajay,

Hello! Hope you had a great last week. Here are the top ML Research Papers recommended by Elvis Saravia in his NLP Newsletter:

### Paper 1 - [KAN: Kolmogorov-Arnold Networks](https://arxiv.org/pdf/2404.19756)
This paper proposes Kolmogorov-Arnold Networks (KANs) as alternatives to Multi-Layer Perceptrons (MLPs); KANs apply learnable activation functions on edges that represent the weights; with no linear weights used, KANs can outperform MLPs and possess faster neural scaling laws; the authors show that KANs can be used as collaborators to help scientists discover mathematics and physical laws.

**Authors, in order of their mention in the paper:**
1. **Ziming Liu:** Ziming Liu is a physicist and a machine learning researcher. He is currently a third-year PhD student at the Massachusetts Institute of Technology and the The NSF Institute for Artificial Intelligence and Fundamental Interactions, advised by Max Tegmark. Liu's research interests lie generally in the intersection of artificial intelligence (AI) and physics (science in general). Here's how to reach out to Liu -
**Website:** https://kindxiaoming.github.io/
**LinkedIn:** https://www.linkedin.com/in/ziming-liu-25a6021a7/
**E-mail:** [e-mail]

2. **Yixuan Wang:** Yixuan Wang is a G3 PhD Candidate of Applied + Computational Mathematics at the California Institute of Technology. His research interests broadly lie in Numerical Analysis, Partial Differential Equation, Applied Probability, and AI for Science. He can be reached out via -
**Website:** https://roywangyx.github.io/index.html
**LinkedIn:** https://www.linkedin.com/in/yixuan-wang-19a6a3159/
**E-mail:** [e-mail]

3. **Sachin Vaidya:** Sachin Vaidya is a postdoctoral associate at the Massachusetts Institute of Technology (MIT) with Prof. Marin Soljačić. He earned his PhD in Physics from Penn State in 2023. One can reach him via -
**Website:** https://www.sachinvaidya.com/
**LinkedIn:** https://www.linkedin.com/in/sachin-vaidya-b5bb39236/
**E-mail:** [e-mail]

4. **Fabian Ruehle:** Fabian Ruehle is an Assitant Professor of Physics and Mathematics at Northeastern University. He is also associated with the NSF Institute for Artificial Intelligence and Fundamental Interactions His main research interest is string theory, but he works also on mathematical and computational aspects of physics, theoretical particle physics and cosmology. Here's how to reach him -
**Website:** https://ruehlef.github.io/
**E-mail:** [e-mail]

5. **James Halverson:** James Halverson is an Associate Professor of Physics at Northeastern University in Boston, Massachusetts. His research is at some of the interfaces between string theory, particle physics, cosmology, mathematics, and deep learning. He can be reached via -
**Website:** http://www.jhhalverson.com/
**LinkedIn:** https://www.linkedin.com/in/james-halverson-6b780723/
**E-mail:** [e-mail]

6. **Marin Soljačić:** Marin Soljačić is a Croatian-American physicist and electrical engineer known for wireless non-radiative energy transfer. He teaches at the Massachusetts Institute of Technology, and is also associated with the NSF Institute for Artificial Intelligence and Fundamental Interactions. One can reach out to him via -
**MIT Profile:** https://physics.mit.edu/faculty/marin-soljacic/
**LinkedIn:** https://www.linkedin.com/in/marin-soljacic-635a353/
**E-mail:** [e-mail]

7. **Thomas Y. Hou:** Thomas Yizhao Hou is the Charles Lee Powell Professor of Applied and Computational Mathematics in the Department of Computing and Mathematical Sciences at the California Institute of Technology. He is known for his work in numerical analysis and mathematical analysis. One can connect with him via -
**Caltech profile:** https://www.cms.caltech.edu/people/hou
**LinkedIn:** https://www.linkedin.com/in/thomas-hou-1a82ab29/
**E-mail:** [e-mail]

8. **Max Erik Tegmark:** Max Erik Tegmark is a Swedish-American physicist, machine learning researcher and author. He is best known for his book Life 3.0 about what the world might look like as artificial intelligence continues to improve. He teaches at the Massachusetts Institute of Technology, and is also associated with the NSF Institute for Artificial Intelligence and Fundamental Interactions. To reach out to him, one can consider the following options -
**MIT Profile:** https://physics.mit.edu/faculty/max-tegmark/
**LinkedIn:** https://www.linkedin.com/in/max-tegmark-68a99898/
**E-mail:** [e-mail]

### Paper 2 - [Better & Faster Large Language Models via Multi-token Prediction](https://arxiv.org/pdf/2404.19737)
This paper proposes a multi-token prediction approach that performs language modeling by training the predict the following n tokens using n independent output heads; the output heads operate on top of a shared transformer trunk; multi-token prediction is shown to be useful when using larger model sizes and can speed up inference up to 3x; the proposed 13B parameter models solves 12 % more problems on HumanEval and 17 % more on MBPP than comparable next-token models.

**Authors, in order of their mention in the paper:**
1. **Fabian Gloeckle:** Fabian Gloeckle is pursuing a PhD from the École des ponts ParisTech and the Fundamental AI Research team (FAIR) at Meta. He is interested in Machine Learning for mathematics and programming. He can be reached out via -
**X:** https://twitter.com/FabianGloeckle
**HuggingFace:** https://huggingface.co/faaabian
**E-mail:** [e-mail]

2. **Badr Youbi Idrissi:** Badr Youbi Idrissi is a research assistant at the Fundamental AI Research team (FAIR) at Meta. He is pursuing his PhD from the LISN - Université Paris-Saclay. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/badr-y-idrissi/?originalSubdomain=fr
**github:** https://github.com/BadrYoubiIdrissi
**E-mail:** [e-mail]

3. **Baptiste Roziere:** Baptiste is a research scientist at Meta AI in Paris working in the code generation team. He works on large language models, with a special interest in applications to code. Baptiste contributed to Llama and started Code Llama. One can reach out to him through -
**LinkedIn:** https://www.linkedin.com/in/baptisteroziere/
**github:** https://github.com/brozi
**X:** https://twitter.com/b_roziere
Unfortunately, we could not find any E-mail ID associated with Roziere.

4. **David Lopez-Paz:** David is a research scientist at the Fundamental AI Research team (FAIR), Meta, where he develops theory and algorithms to discover causation from data, in order to create robust learning machines. One can reach him through -
**Meta Profile:** https://ai.meta.com/people/1565619390678045/david-lopez-paz/
**github:** https://github.com/lopezpaz
Unfortunately, we could not find any E-mail ID associated with Lopez-Paz.

5. **Gabriel Synnaeve:** Gabriel Synnaeve is a research scientist on the Fundamental AI Research team (FAIR) at Meta, who joined as a postdoctoral researcher in 2015. Prior to Facebook, Gabriel was a postdoctoral fellow in Emmanuel Dupoux’s team at École Normale Supérieure in Paris, working on reverse-engineering the acquisition of language in babies. He can be reached via -
**LinkedIn:** https://www.linkedin.com/in/gabrielsynnaeve/?originalSubdomain=fr
**X:** https://twitter.com/syhw
**E-mail:** [e-mail]

### Paper 3 - [Capabilities of Gemini Models in Medicine](https://arxiv.org/pdf/2404.18416)
This paper presents a family of multimodal models specialized in medicines and based on the strong multimodal and long-context reasoning capabilities of Gemini; achieves state-of-the-art performance on 10/14 benchmarks surpassing GPT-4 models; it achieves 91% accuracy on MedQA (USMLE) benchmark using an uncertainty-guided search strategy.

**Authors, in order of their mention in the paper:**
1. **Khaled Saab:** Khaled Saab is a Research Scientist at Google DeepMind. He has a PhD and MS in Electrical Engineering from Stanford University. He can be reached through -
**Website:** https://khaledsaab.github.io/
**LinkedIn:** https://www.linkedin.com/in/khaled-saab-181034122/
**X:** https://twitter.com/KhaledSaab11
**E-mail ID:** [e-mail]

2. **Tao Tu:** Tao Tu is a Senior Software Engineer at Google Research. His research is focused on using multimodal neuroimaging techniques to understand the human brain. He is interested in applying machine learning and statistical methods to solve problems in cognitive and clinical neuroscience. He can be reached via -
**LinkedIn:** https://www.linkedin.com/in/tao-tu-024a013b/
**X:** https://twitter.com/taotu831
**E-mail ID:** [e-mail]

3. **Wei-Hung Weng:** Wei-Hung Weng is a Research Scientist at Google. He finished his PhD from the Massachusetts Institute of Technology in 2022. Here's how he can be reached -
**Website:** https://ckbjimmy.github.io/
**LinkedIn:** https://www.linkedin.com/in/ckbjimmy/
**E-mail ID:** [e-mail]

4. **Ryutaro Tanno:** Ryutaro Tanno is a Research Scientist at Google DeepMind. His research focuses on developing high-performance machine learning algorithms which are risk-aware, interpretable and robust for safe use in healthcare applications. He can be reached via -
**Website:** https://rt416.github.io/
**github:** https://github.com/rt416
**X:** https://twitter.com/ryutarot92
**E-mail ID:** [e-mail]

5. **David Stutz:** David Stutz is a research scientist at Google DeepMind interested in making generative AI safe for everyone to use through research on uncertainty estimation, watermarking, adversarial robustness, or out-of-distribution detection, among other topics. One can reach him via -
**Website:** https://davidstutz.de/
**LinkedIn:** https://www.linkedin.com/in/davidstutz92/
**X:** https://twitter.com/davidstutz
**E-mail ID:** [e-mail]

6. **Ellery Wulczyn:** Ellery Wulczyn is a research scientist, software engineer and tech lead exploring the frontier of human-centered AI in health and medicine. Currently employed with Google, his recent work includes research on LLMs for medical question answering, foundation models for histopathology, and prognostic AI as a tool for knowledge discovery. Here's how to reach him -
**Website:** https://ewulczyn.github.io/about/
**LinkedIn:** https://www.linkedin.com/in/ellery/
**E-mail ID:** [e-mail]

7. **Fan Zhang:** Fan Zhang is a Staff Software Engineer at Google. Their interest involves Natural Language Processing and Human Computer Interaction. Their PhD research focuses on using NLP techniques for revision analysis. Here's how one can reach them -
**LinkedIn:** https://www.linkedin.com/in/fan-zhang-45113949/
**E-mail ID:** : [e-mail]

8. **Tim Strother:** Tim Strother is a Senior Software Engineer at Google. He is interested in architecture, art, philosophy, and software development. He can be reached through -
**LinkedIn:** linkedin.com/in/timstrother
We unfortunately couldn't find any other contact information for Strother.

9. **Chunjong Park:** Chunjong Park is a software engineer at Google Research. His research lies at the intersection of multimodal LLMs and health. Here's how one can reach him -
**Website:** https://cjpark.xyz/
**LinkedIn:** https://www.linkedin.com/in/cjpark/
**E-mail ID:** [e-mail]

10. **Elahe Vedadi:** Elahe Vedadi is a software engineer at Google Research. She obtained her PhD in Electric, Electronic and Communications Engineering from the University of Illinois Chicago. Her research interests are Distributed Machine Learning, Coding Theory, Edge Computing, Tensor Computations and Linear Algebra. One can reach her through -
**Website:** https://elahevedadi.wixsite.com/elahevedadi
**LinkedIn:** https://www.linkedin.com/in/elahe-vedadi/
**E-mail ID:** [e-mail]

11. **Juanma Zambrano Chaves:** Juan Manuel Zambrano Chaves is a Physician scientist interested in developing novel methods to analyze medical data and creating tools that help improve people's health. He is pursuing a PhD in biomedical science from Stanford University. He can be reached via -
**Website:** https://jmzam.github.io/
**LinkedIn:** https://www.linkedin.com/in/juanmzambrano/
**X:** https://twitter.com/JMZambranoC
Unfortunately, we couldn't find an E-mail ID associated with Juan Manuel Zambrano Chaves in the public domain.

12. **Szu-Yeu Hu:** Szu-Yeu Hu is a Machine Learning Engineer at Google Health AI. He is interested in the integration of data from different sources, including genomic, social-behavioral, environmental and clinical data. He has a Master's Degree in Biomedical Informatics from Harvard Medical School. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/szuyeuhu/
**HuggingFace:** https://huggingface.co/sdcjimmy
Unfortunately, we could not find any E-mail ID associated with Szu-Yeu Hu in the public domain.

13. **Mike Schaekermann:** Mike Schaekermann is a Research Scientist at Google Health. His research is located at the intersection of human-computer interaction (HCI), artificial intelligence (AI) and medicine. He can be contacted via -
**Website:** https://www.mikeshake.me/
**LinkedIn:** https://www.linkedin.com/in/mschaeke/
**X:** https://twitter.com/hardyshakerman
Unfortunately, we could not find any E-mail ID associated with Mike Schaekermann in the public domain.

14. **Aishwarya Kamath:** Aishwarya Kamath is a research scientist at Google DeepMind. Her current interests lie at the intersection of vision and language, and her research focuses on using information from multiple sources such as text, images, and video to improve reasoning capabilities of machines. She can be contacted via -
**Website:** https://ashkamath.github.io/
**github:** https://github.com/ashkamath/
**X:** https://twitter.com/ashkamath20
**E-mail ID:** [e-mail]

15. **Yong Cheng:** Yong Cheng is a Senior Staff Research Engineer at Google DeepMind. He obtained his PhD from Tsinghua University. He can be contacted through -
**LinkedIn:** https://www.linkedin.com/in/yong-cheng-a29068230/
Unfortunately, we could not find any other contact details for Yong Cheng.

16. **David G.T. Barrett:** David G.T. Barrett is a research scientist at Google DeepMind. His research interests include Neural Networks, Sparse coding, Variational Inference, The Helmholtz Machine, Auto-encoding, Optimal compensation theory, Quadratic Programming, Balanced network theory, Noise correlations, Visual cortex tuning, Natural sound processing and Information theory. He can be contacted via -
**X:** https://twitter.com/dgtbarrett
**E-mail ID:** [e-mail]

17. **Cathy Cheung:** Cathy Cheung is a Senior Software Engineer at Google. She has a bachelor's degree in Computer Science from the University of California, Berkeley. Here's how she can be contacted -
**LinkedIn:** https://www.linkedin.com/in/cathy-cheung-123b442b/

18. **Basil Mustafa:** Basil Mustafa is a research engineer at Google Deepmind in Zürich, predominately working on Gemini. His research background is in computer vision, representation learning and dynamic sparse models, alongside threads relating to medical imaging and learning under label noise. He can be reached via -
**Website:** https://www.basilmustafa.com/
**LinkedIn:** https://www.linkedin.com/in/basil-mustafa/
**X:** https://twitter.com/_basilM
**E-mail ID:** [e-mail]

19. **Anil Palepu:** Anil Palepu is a PhD Candidate at the Harvard-MIT Program in Health Sciences and Technology, and a student researcher at Google. He is interested in self-supervised learning, vision models, and language models, especially as these relate to the medical domain. He can be contacted via -
**Website:** https://apalepu13.github.io/
**LinkedIn:** https://www.linkedin.com/in/anilpalepu
**X:** https://www.twitter.com/apalepu13
**E-mail ID:** [e-mail]

20. **Daniel McDuff:** Daniel McDuff is a Staff Research Scientist at Google. His research is at the intersection of computer science, psychology and biomedical engineering. He can be contacted via -
**LinkedIn:** https://www.linkedin.com/in/daniel-mcduff-19968051/
**X:** https://twitter.com/danmcduff
Unfortunately, we could not find any E-mail ID associated with Daniel McDuff in the public domain.

21. **Le Hou:** Le Hou is a Staff Software Engineer at Google. His research interests include deep learning, computer vision, natural language processing. He can be reached via -
**Website:** https://www.le-hou.com/
**LinkedIn:** https://www.linkedin.com/in/le-hou-b2627681/
**E-mail ID:** [e-mail]

22. **Tomer Golany:** Tomer Golany is Staff Software Engineer and Research Engineering Manager at Verily. He previously worked as a Senior Software Engineer, Technical Lead at Google. Here's how he can be reached -
**LinkedIn:** https://www.linkedin.com/in/le-hou-b2627681/
Unfortunately, we could not find any other contact detail, including an E-mail ID, for Golany.

23. **Luyang Liu:** Luyang Liu is a researcher at Google Research, where he works at the intersection of machine intelligence, mobile systems and digital wellbeing. He got his Ph.D degree from Department of Electrical and Computer Engineering, Rutgers University. Here's how he can be reached -
**Website:** https://www.winlab.rutgers.edu/~luyang/
**LinkedIn:** https://www.linkedin.com/in/luyang-liu-492abb8a/
Unfortunately, we could not find any E-mail ID associated with Luyang Liu in the public domain.

24. **Jean-baptiste Alayrac:** Jean-baptiste Alayrac is a Staff Research Scientist at Google DeepMind. His work focuses on structured learning from video and natural language. More details can be found in my resume. He can be reached via -
**Website:** https://www.jbalayrac.com/
**LinkedIn:** https://www.linkedin.com/in/jean-baptiste-alayrac-269a0565/
**X:** https://twitter.com/jalayrac
**E-mail ID:** [e-mail]

25. **Neil Houlsby:** Neil Houlsby is a Senior Staff Research Scientist at Google Deepmind. He works in machine learning and artificial intelligence, with a focus on vision-language models (VLMs), scalable pre-training, sparsity, modularity, and task adaptation. He can be reached through -
**Website:** https://neilhoulsby.github.io/
**X:** https://twitter.com/neilhoulsby
**E-mail ID:** [e-mail]

26. **Nenad Tomašev:** Nenad Tomašev is a Staff Research Scientist at Google DeepMind. He is passionate about the transformative power of machine learning in helping us tackle the most challenging and impactful problems in the world today, by creating powerful AI systems that benefit humanity. He can be contacted through -
**LinkedIn:** https://www.linkedin.com/in/nenadtomasev/?originalSubdomain=uk
**X:** https://www.twitter.com/weballergy
**E-mail ID:** [e-mail]

27. **Jan Freyberg:** Jan Freyberg is a machine learning software engineer at Google. He is currently working on applied machine learning. He can be reached via -
**Website:** https://www.janfreyberg.com/
**LinkedIn:** https://www.linkedin.com/in/jfreyberg/?originalSubdomain=uk
**X:** https://www.twitter.com/janfreyberg
**E-mail ID:** [e-mail]

28. **Charles Lau:** Charles T. Lau is a research radiologist with Google's Advanced Clinical - Health AI. He's also Associate Clinical Professor at the David Geffen School of Medicine at the University of California, Los Angeles. He can be contacted through -
**LinkedIn:** https://www.linkedin.com/in/charlestlau/
**X:** https://twitter.com/dogstar
**E-mail ID:** [e-mail]

29. **Jonas Kemp:** Jonas Kemp is an ML Software Engineer at Google. His interest lies in Deep learning research for electronic health records modeling and predictions. He can be reached via -
**LinkedIn:** https://www.linkedin.com/in/jonas-kemp-15920a68/
**github:** https://github.com/jonasbkemp
Unfortunately, we could not find any E-mail ID associated with Jonas Kemp in the public domain.

30. **Jeremy Lai:** Jeremy Lai is a Software Engineer at Google. He has a Master's Degree in Computer Engineering from the Massachusetts Institute of Technology. He can be contacted through -
**LinkedIn:** https://www.linkedin.com/in/jeremy-lai-5b271712/
Unfortunately we could not find any other contact details, including any e-mail ID, for Jeremy Lai in the public domain.

31. **Shekoofeh Azizi:** Shekoofeh Azizi is a staff research scientist and a research lead at Google DeepMind. Her research is focused on developing approaches that facilitate the translation of AI solutions into tangible clinical impact. She can be contacted through -
**Website:** https://www.shekoofehazizi.com/
**LinkedIn:** https://www.linkedin.com/in/shekoofehazizi/?originalSubdomain=ca
**X:** https://twitter.com/AziziShekoofeh
**E-mail ID:** [e-mail]

32. **Kimberly Kanada:** Kimberly Kanada is a dermatologist based in Sunnyvale, Silicon Valley, California. She practices at the Sutter Health - Palo Alto Medical Foundation. She can be reached via -
**Sutter Health profile:** https://www.sutterhealth.org/find-doctor/dr-kimberly-kanada
**LinkedIn:** https://www.linkedin.com/in/kimberly-kanada-0661b7157/
Unfortunately, we could not find any other contact details, including an e-mail ID, for Dr. Kanada. Her profile on Sutter Health's website, however, does include a phone number.

33. **SiWai Man:** SiWai Man is Global Program Manager at Google Health. Currently based in The Randstand, Netherlands, he is responsible for the global vendor management program with +100 workers in Google Health to help improve health initiatives across Google product areas including Fitbit, Google Search, YouTube and Medical Large Language Models Med-Palm. He can be contacted via -
**LinkedIn:** https://www.linkedin.com/in/siwaiman/
Unfortunately, we could not find any other contact information, including an E-mail ID, for SiWai Man.

34. **Kavita Kulkarni:** Kavita Kulkarni is a research engineer at Google Research. She is working towards integrating Artificial Intelligence in health research. She can be reached via -
**LinkedIn:** https://www.linkedin.com/in/kavitakulkarni1/
**Instagram:** https://www.instagram.com/kavitakoolkarni/
Unfortunately, we could not find any other contact information, including an E-mail ID, for Kavita Kulkarni.

35. **Ruoxi Sun:** Ruoxi Sun is a Senior Research Scientist, Cloud AI Research, at Google. She obtained her PhD in Machine Learning, Statistics, and Computational Biology from Columbia University in 2019. Here's how one can reach her -
**LinkedIn:** https://www.linkedin.com/in/ruoxi-sun-84a85457/
Unfortunately, we could not find any other contact information, including an E-mail ID, for Ruoxi Sun.

36. **Siamak Shakeri:** Siamak Shakeri is a research scientist at Google DeepMind. He has experience with Applying Machine Learning and Natural Language Processing techniques to solve large scale question answering problems and with designing, implementing and improving Deep Learning models to real world NLP applications. He can be reached via -
**LinkedIn:** https://www.linkedin.com/in/siamak-shakeri-b0827316/
Unfortunately, we could not find any other contact information, including an E-mail ID, for Siamak Shakeri.

37. **Luheng He:** Luheng He is a esearch scientist at Google AI. Her esearch interests include natural language processing and computational linguistics. She can be contacted via -
**Website:** https://luheng.github.io/
**LinkedIn:** https://www.linkedin.com/in/luheng-he-24207728/
**X:** https://www.twitter.com/LuhengH
**E-mail ID:** [e-mail]

38. **Ben Caine:** Ben Caine is a Research Engineer at Google DeepMind working on Gemini with a focus on multimodality and instruction tuning. He can be contacted through -
**Website:** http://bencaine.me/
**LinkedIn:** https://www.linkedin.com/in/bcaine/
**github:** https://github.com/bcaine
**E-mail ID:** [e-mail]

39. **Albert Webson:** Albert Webson is a Senior Research Scientist at Google DeepMind. He is a core contributor to both Gemini pretraining and Bard RLHF. Additionally, he works on situational awareness and model organism. He can be reached through -
**Website:** https://representation.ai/
**github:** https://github.com/awebson
**X:** https://twitter.com/albertwebson
Unfortunately, we could not find any e-mail ID associated with Albert Webson in the public domain.

40. **Natasha Latysheva:** Natasha Latysheva is a Research Engineer at Google DeepMind. Her work focuses on natural language processing and machine translation. Here's how one can reach her -
**LinkedIn:** https://www.linkedin.com/in/nslatysheva/
**X:** https://twitter.com/n_latysheva
Unfortunately, we could not find any e-mail ID associated with Natasha Latysheva in the public domain.

41. **Melvin Johnson:** Melvin Johnson is a Staff Software Engineer at Google Research. He works on Machine Translation and Natural Language Processing. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/melvinjosej/
**X:** https://twitter.com/melvinjohnsonp
Unfortunately, we could not find any e-mail ID associated with Melvin Johnson in the public domain.

42. **Philip Mansfield:** Philip Andrew Mansfield is a Staff Software Engineer, Research and Machine Intelligence at Google. His recent work is in Computer Vision, Pattern Recognition and Machine Learning, including recognition of people and other content in camera images, and recognition of document structure and semantics in PDF page images. He can be contacted through -
**LinkedIn:** https://www.linkedin.com/in/philipmansfield/
We unfortunately could not find any other contact information, including an e-mail ID, for Philip Mansfield.

43. **Jian Lu:** Jian Lu is Director of Software Engineering at Google Health AI. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/philipmansfield/
Unfortunately, we could not find any other contact information, including an e-mail ID, for Jian Lu.

44. **Ehud Rivlin:** Ehud Rivlin is an engineer and researcher at Google. He can be contacted via -
**LinkedIn:** https://www.linkedin.com/in/ehud-rivlin-8271b918/
Unfortunately, we could not find any other contact information, including an e-mail ID, for Ehud Rivlin in the public domain.

45. **Jesper Anderson:** Unfortunately, we could not find any information on any researcher associated in any capacity with Google named Jesper Anderson.

46. **Bradley Green:** Bradley Green is Engineering Director, Research and Machine Intelligence at Google. Here's how one can reach her -
**LinkedIn:** https://www.linkedin.com/in/brad-green-b0247915/
Unfrotunately, we could not find any other contact information, including an e-mail ID, for Bradley Green in the public domain.

47. **Renee Wong:** Renee Wong is a product manager at Google Research - Health AI. She is passionate about improving access to healthcare globally through technology and innovation. Here's how one can reach her -
**LinkedIn:** https://www.linkedin.com/in/reneeewong/
**X:** https://twitter.com/reneeewong
Unfortunately, we could not find an e-mail ID associated with Renee Wong in the public domain.

48. **Jonathan Krause:** Jonathan Krause is a researcher at Google. He studied at Stanford University. Here's how one can contact him -
**Homepage:** https://ai.stanford.edu/~jkrause/
**X:** https://twitter.com/jkrause314
Unfortunately, we could not find any other contact information on Jonathan Krause, including an e-mail ID, in the public domain.

49. **Jonathon Shlens:** Jonathon Shlens is a principal scientist and research director at Google DeepMind interested in vision, language and learning. I lead organizations interested a basic and applied research focused on machine learning, computer vision and basic science research. Here's how he can be contacted -
**Website:** https://shlens.github.io/
**LinkedIn:** https://www.linkedin.com/in/shlens/
**github:** https://github.com/shlens
**E-mail ID:** [e-mail]

50. **Ewa Dominowska:** Ewa Dominowska is a Senior Director at Google. She has authored several papers and dozens of patents in the areas of online advertising, search, pricing models, predictive algorithms and user interaction. She can be reached via -
**LinkedIn:** https://www.linkedin.com/in/everdom/
**Facebook:** https://www.facebook.com/ewa.dominowska.5/
Unfortunately, we could not find any e-mail ID associated with Ewa Dominowska in the public domain.

51. **S. M. Ali Eslami:** S. M. Ali Eslami is Director of Research Strategy, Gemini at Google DeepMind. He is also an angel investor. Here's how he can be contacted -
**Website:** https://arkitus.com/research/
**LinkedIn:** https://www.linkedin.com/in/smalieslami/
**X:** https://twitter.com/arkitus
**E-mail ID:** [e-mail]

52. **Katherine Chou:** Katherine Chou is Senior Director, Research & Innovations at Google with a specific focus on nurturing scientific and technical breakthroughs with global impact for health, climate change, and advancement of platform technologies for our developers and researchers. Here's how she can be reached -
**LinkedIn:** https://www.linkedin.com/in/katherinechou/
Unfortunately, we could not find any e-mail ID associated with Katherine Chou.

53. **Claire Cui:** Claire Cui is Vice President & Engineering Fellow at Google DeepMind. She was a founding engineer for Google’s AdSense for Content product. She later helped co-found Google Health Research and Medical Brain to work on machine learning for improving people's health. Here's how one can reach her -
**LinkedIn:** https://www.linkedin.com/in/claire-cui-5021035/
Unfortunately, we could not find any e-mail ID associated with Dr. Claire Cui in the public domain.

54. **Oriol Vinyals:** Oriol Vinyals is Vice President of Research, Gemini Technical Lead at Google DeepMind. He focuses his efforts on both understanding and developing of new ideas around machine learning, neural networks, and reinforcement learning. Here's how one can contact him -
**Website:**
**LinkedIn:** https://www.linkedin.com/in/oriol-vinyals-00b3366/
**X:** https://twitter.com/oriolvinyalsml
Unfortunately, we could not find any e-mail ID associated with Oriol Vinyals in the public domain.

55. **Koray Kavukcuoglu:** koray kavukcuoglu is Vice President of Research at Google DeepMind. He has a PhD in Computer Science from New York University. He is based in London. He can be reached through -
**Website:** https://koray.kavukcuoglu.org/index.html
**LinkedIn:** https://www.linkedin.com/in/koray-kavukcuoglu-0439a720/
**X:** https://twitter.com/koraykv
**E-mail ID:** [e-mail]

56. **James Manyika:** James Manyika is Senior Vice President at Google-Alphabet reporting to the CEO. He leads Research, Technology & Society, including overseeing Google Labs and Google Research. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/jamesmanyika/
Unfortunately, we could not find any other contact information, including any e-mail ID, for James M. Manyika in the public domain.

57. **Jeff Dean:** Jeff Dean is Chief Scientist at Google Research and Google DeepMind. He has a PhD in Computer Science from Washington University.
**LinkedIn:** https://www.linkedin.com/in/jeff-dean-8b212555/
**X:** https://twitter.com/jeffdean
Unfortunately, we could not find any e-mail ID associated with Jeff Dean in the public domain.

58. **Demis Hassabis:** Demis Hassabis is the co-founder and CEO of Google DeepMind, which he founded independently in 2014. His research connecting memory with imagination was listed in the top ten scientific breakthroughs of 2007 by the journal Science. Here's how one can contact him -
**LinkedIn:** https://www.linkedin.com/in/demishassabis/
**X:** https://twitter.com/demishassabis/
**E-mail ID:** [e-mail]

59. **Yossi Matias:** Yossi Matias is Vice President, Engineering and Research, at Google. His work on Health AI is aiming to help transform healthcare - from driving better diagnostics to Med-PaLM, a language model tuned for the health industry. Here's how one can reach him -
**LinkedIn:** https://www.linkedin.com/in/yossimatias/
**X:** https://twitter.com/ymatias
**E-mail ID:** [e-mail]

60. **Dale Webster:** Dale Webster is Director of Research at Google Health working to improve patient outcomes in healthcare using Deep Learning and Medical Imaging. Here's how one can contact him -
**LinkedIn:** https://www.linkedin.com/in/dale-webster-4b98913/
**E-mail ID:** [e-mail]

61. **Joëlle Barral:** Joëlle Barral is a Senior Director of Research & Engineering at Google DeepMind, leading AI research teams across the US, Canada and Europe. Here's how she can be contacted -
**LinkedIn:** https://www.linkedin.com/in/joellebarral/
**X:** https://twitter.com/joelle_barral
Unfortunately, we could not find any E-mail ID associated with Joëlle Barral in the public domain.

62. **Greg Corrado:** Greg Corrado is a Scientist at Google Research. In 2011 he co-founded the Google Brain Team, which has helped to catalyze the broad adoption of deep neural networks across technology companies worldwide. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/greg-corrado-phd/
**Facebook:** https://www.facebook.com/greg.corrado.phd/
**X:** https://twitter.com/greg_corrado
**E-mail ID:** [e-mail]

63. **Christopher Semturs:** Christopher Semturs is Senior Staff Engineering Manager at Google Health Research. He is working on AI projects to improve Health Outcomes, advancing research in Generative AI, Large Language Models, and Medical Imaging. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/semturs/
Unfortunately, we could not find any other contact information, including an e-mail ID, for Christopher Semturs in the public domain.

64. **S. Sara Mahdavi:** S. Sara Mahdavi is Technical Program Manager at Google DeepMind. She is a researcher in the field of biomedical imaging for medical interventions, and passionate about finding practical solutions to common problems, particularly in healthcare and ML. She can be contacted via -
**LinkedIn:** https://www.linkedin.com/in/s-sara-mahdavi/?originalSubdomain=ca
Unfortunately, we could not find any other contact information, including an e-mail ID, for S. Sara Madahvi in the public domain.

65. **Juraj Gottweis:** Juraj Gottweis is a Google Fellow. Here's how he can be reached -
**LinkedIn:** https://www.linkedin.com/in/gottweis/?originalSubdomain=ch
**X:** https://twitter.com/Mysiak
Unfortunately, we could not find any other contact information, including an e-mail ID, for Juraj Gottweis in the public domain.

66. **Alan Karthikesalingam:** Alan Karthikesalingam is a Senior Staff Clinician Scientist at Google. He has expertise in Digital Health and Artificial Intelligence for Healthcare. He can be reached via -
**LinkedIn:** https://www.linkedin.com/in/alankarthi/
**X:** https://twitter.com/alan_karthi?lang=en
**E-mail ID:** [e-mail]

67. **Vivek Natarajan:** Vivek Natarajan is a Research Scientist at Google leading research at the intersection of large language models (LLMs) and biomedicine. In particular, Vivek is the lead researcher behind Med-PaLM and Med-PaLM 2, which were the first AI systems to obtain passing and expert level scores on US Medical License exam questions respectively. He can be reached through -
**Website:** https://https://natviv.me/
**LinkedIn:** https://www.linkedin.com/in/vivek-natarajan-a3670118/
**X:** (https://twitter.com/vivnat)
**E-mail ID:** [e-mail]

### Paper 4 - [When to Retrieve: Teaching LLMs to Utilize Information Retrieval Effectively](https://arxiv.org/pdf/2404.19705)
This paper presents an approach to train LLMs to effectively utilize information retrieval; it first proposes a training approach to teach an LLM to generate a special token,<RET>, when it's not confident or doesn't know the answer to a question; the fine-tuned model outperforms a base LLM in two fixed alternate settings that include never retrieving and always retrieving context.

**Authors, as per the order of their mention in the paper:**
1. **Tiziano Labruna:** Tiziano Labruna is a researcher PhD student at Fondazione Bruno Kessler. He works on the topic of data-driven conversational agents within the Natural Language Processing research group. Here's how to reach him -
**LinkedIn:** https://www.linkedin.com/in/tiz/?originalSubdomain=it
**X:** https://twitter.com/t_labruna
**E-mail ID:** [e-mail]

2. **Jon Ander Campos:** Jon Ander Campos was a researcher associated with the HiTZ Center - Ixa, University of the Basque Country UPV/EHU at the time of the writing of the above paper. He is currently a Member of the Staff at Cohere. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/jon-ander-campos/?locale=en_US
**LinkedIn:** https://www.linkedin.com/in/jon-ander-campos/?locale=en_US
**X:** https://twitter.com/jaa_campos
**E-mail ID:** [e-mail]

3. **Gorka Azkune:** Gorka Azkune is a computer scientist enthusiast about research and science popularization. His work experience has been focused on developing several autonomous systems, where perception and cognition are the tools to operate in human populated environments. One can reach out to him via -
**Website:** https://gazkune.github.io/
**LinkedIn:** https://www.linkedin.com/in/gorka-azkune-80780035/?originalSubdomain=es
**E-mail ID:** [e-mail]

### Paper 5 - [RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing](https://arxiv.org/pdf/2404.19543)
This paper covers the most important recent developments in RAG and RAU systems; it includes evolution, taxonomy, and an analysis of applications; there is also a section on how to enhance different components of these systems and how to properly evaluate them; it concludes with a section on limitations and future directions.

**Authors, as per the order of their mention in the paper:**
1. **Yucheng Hu:** Yucheng Hu is a researcher at East China University of Science and Technology. Here's how one can reach them -
**E-mail ID:** [e-mail]
Unfortunately, we could not find any other details on Hu in the public domain.
2. **Yuxing Lu:** Yuxing Lu is a PhD student at Department of BigData and Biomedical AI, College of Future Technology, Peking University. He is currently a research intern at Tencent. Here's how to reach him -
**LinkedIn:** https://www.linkedin.com/in/yuxinglu0613/?originalSubdomain=cn
**github:** https://github.com/YuxingLu613
**E-mail ID:** [e-mail]

### Paper 6 - [Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models](https://arxiv.org/pdf/2405.01535)
This paper introduces Prometheus 2, a refined and more powerful update to Prometheus, a language model that evaluates other Large Language Models (LLMs). Prometheus 2 closely mirrors human and GPT-4 judgements, and is capable of processing both direct assessment and pair-wise ranking formats grouped with a user-defined evaluation criteria. On four direct assessment benchmarks and four pairwise ranking benchmarks, Prometheus 2 scores the highest correlation and agreement with humans and proprietary LM judges among all tested open evaluator LMs.

**Authors, as per the order of their mention in the paper:**

1. **Seungone Kim:** Seungone Kim is an MS student at the Kim Jaechul Graduate School of AI at Korea Advanced Institute of Science and Technology (KAIST AI), advised by Minjoon Seo. He is an incoming PhD student at the Carnegie Mellon University's Language Technologies Institute. He is also associated with LG AI Research. He can be reached via -
**Website:** https://seungonekim.github.io/
**LinkedIn:** https://www.linkedin.com/in/seungone-kim-09b551264/?originalSubdomain=kr
**E-mail ID:** [e-mail]

2. **Juyoung Suk:** Juyong Suk is an MS student at the Kim Jaechul Graduate School of AI at Korea Advanced Institute of Science and Technology (KAIST AI), advised by Minjoon Seo. He is interested in developing evaluation methods for LLMs, VLMs, and others and utilizing them to enhance their ability. Here's how he can be reached -
**github:** https://github.com/scottsuk0306
**LinkedIn:** https://www.linkedin.com/in/juyoung-suk-b5175a192/
**huggingface:** https://huggingface.co/scottsuk0306
**E-mail ID:** [e-mail]

3. **Shayne Longpre:** Shayne Longpre is a PhD candidate at MIT Media Lab with a focus on data-centric AI, language models, and their societal impact. Here's how to reach him -
**Website:** https://www.shaynelongpre.com
**LinkedIn:** https://www.linkedin.com/in/shayne-redford-longpre/
**E-mail ID:** [e-mail]

4. **Bill Yuchen Lin:** Bill Yuchen Lin is a researcher at the Allen Institute for AI. He is based in Seattle, Washington, United States. He has a PhD in Computer Science from the University of Southern California. He can be reached through -
**Website:** https://yuchenlin.xyz/
**HuggingFace:** https://huggingface.co/yuchenlin
**X:** https://twitter.com/billyuchenlin
**E-mail ID:** [e-mail]

5. **Jamin Shin:** Jamin Shin is a Research Scientist at NAVER AI Lab. Mainly working with Large Language Models (LLMs), he is interested in getting rid of human annotation/evaluations in the Generative AI scene. He can be reached via -
**Website:** https://www.jayshin.xyz/
**LinkedIn:** https://www.linkedin.com/in/jayshin94/
**github:** https://github.com/jshin49
**X:** https://twitter.com/jshin491
**E-mail ID:** [e-mail]

6. **Sean Welleck:** Sean Welleck is an Assistant Professor in the Language Institute of the School of Computer Science at the Carnegie Mellon University. His research focuses on deep learning and generative models. He can be reached via -
**Website:** https://wellecks.com/
**LinkedIn:** https://www.linkedin.com/in/sean-welleck-324b843a/
**X:** https://www.twitter.com/wellecks
**E-mail ID:** [e-mail]

7. **Graham Neubig:** Graham Neubig is an Associate Professor at the Language Technology Institute in the School of Computer Science at the Carnegie Mellon University. His research focuses on machine learning and natural language processing, with a particular focus on question answering, code generation, multilingual processing, and evaluation/interpretability. He can be reached via -
**Website:** https://phontron.com/
**LinkedIn:** https://www.linkedin.com/in/graham-neubig-10b41616b/
**X:** https://www.twitter.com/gneubig
**E-mail ID:** [e-mail]

8. **Moontae Lee:** Moontae Lee is an Assistant Professor, Department of Information and Design Sciences at the UIC Business School, University of Illinois Chicago. He is also part of the Fundamental Research Laboratory of LG AI Research. Here's how one can reach him -
**Website:** https://moontae.people.uic.edu/
**LinkedIn:** https://www.linkedin.com/in/moontae-lee-975248123/
**X:** https://twitter.com/chobbangi
**E-mail ID:** [e-mail]

9. **Kyungjae Lee:** Kyungjae Lee is a research scientist specialising in Natural Language Processing at LG AI Research. He has a PhD from the Language and data Intelligence Lab of the Department of Computer Science at Yonsei University. He can be reached via -
**Website:** https://lkj0509.github.io/
**LinkedIn:** https://www.linkedin.com/in/%EA%B2%BD%EC%9E%AC-%EC%9D%B4-0509b1118/
**E-mail ID:** [e-mail]

10. **Minjoon Seo:** Minjoon Seo is an Assistant Professor at KAIST AI, where he is the Director of Language & Knowledge Lab, and the Chief Scientist of Twelve Labs. He is interested in how the world knowledge can be encoded and accessed, and how new knowledge can be discovered. Here's how to reach him -
**Website:** https://seominjoon.github.io/
**LinkedIn:** https://www.linkedin.com/in/minjoon/?originalSubdomain=kr
**E-mail:** [e-mail]

### Paper 7 - [Self-Play Preference Optimization for Language Model Alignment](https://arxiv.org/pdf/2405.00675)
This paper proposes a self-play-based method for aligning language models; this optimation procedure treats the problem as a constant-sum two-player game to identify the Nash equilibrium policy; it addresses the shortcomings of DPO and IPO and effectively increases the log-likelihood of chose responses and decreases the rejected ones; SPPO outperforms DPO and IPO on MT-Bench and the Open LLM Leaderboard.

**Authors, as per their order of mention in the paper:**

1. **Yue Wu:** a final-year Ph.D. student at Department of Computer Science, University of California, Los Angeles (UCLA), advised by Prof. Quanquan Gu. His research interest covers various aspects of machine learning theory, including deep learning and reinforcement learning. He can be reached through -
**Website:** https://yuewu.us/
**github:** https://github.com/MeckyWu
**X:** https://twitter.com/FrankYueWu1
**E-mail ID:** [e-mail]

2. **Zhiqing Sun:** Zhiqing Sun is a final-year Ph.D. candidate at CMU LTI, advised by Prof. Yiming Yang. He is generally interested in machine learning and artificial intelligence, particularly in enhancing the reliability of foundation models, including large language models (LLMs) and large multimodal models (LMMs), through minimal human supervision and scalable oversight. Here's how he can be reached -
**Website:** https://www.cs.cmu.edu/~zhiqings/
**LinkedIn:** https://www.linkedin.com/in/zhiqing-sun-5781b3100/
**X:** https://twitter.com/edwardsun0909
**E-mail ID:** [e-mail]

3. **Huizhuo Yuan:** Huizhuo Yuan is a Graduate student at the Artificial General Intelligence Laboratory, University of California, Los Angeles. She is a researcher on LLMs, Diffusion Models, Reinforcement Learning, Games, and AI for Science. Here's how one can reach her -
**LinkedIn:** https://www.linkedin.com/in/huizhuo-y/
**X:** https://twitter.com/HuizhuoY
**E-mail ID:** [e-mail]

4. **Kaixuan Ji:** Kaixuan Ji is a PhD Student of Computer Science at the University of California, Los Angeles. He has a BE from Tsinghua University. He can be reached through -
**HuggingFace:** https://huggingface.co/Jerry46
**X:** https://twitter.com/Kaixuan_Ji_19
**E-mail ID:** [e-mail]

5. **Yiming Yang:** Yiming Yang is a Professor of Language Technologies Institute and Machine Learning Department at the Carnegie Mellon University. Her research has centered on statistical learning methods/algorithms and application to very-large-scale text categorization, web-mining for concept graph discovery, semi-supervised clustering, multitask learning, etc. Here's how to reach her -
**Website:** https://www.cs.cmu.edu/~yiming/
**E-mail ID:** [e-mail]

6. **Quanquan Gu:** Quanquan Gu is an Associate Professor of Computer Science at UCLA. He leads the UCLA Artificial General Intelligence Lab. research is in artificial intelligence and machine learning, with a focus on nonconvex optimization, deep learning, reinforcement learning, Large Language Models (LLMs), and deep generative models (e.g., diffusion models). He can be reached via -
**Website:** https://web.cs.ucla.edu/~qgu/
**LinkedIn:** https://www.linkedin.com/in/quanquan-gu-234a7b21b/
**E-mail ID:** [e-mail]

### Paper 8 - [A Primer on the Inner Workings of Transformer-based Language Models](https://arxiv.org/pdf/2405.00208)

This paper presents a technical introduction to current techniques used to interpret the inner workings of Transformer-based language models; it provides a detailed overview of the internal mechanisms implemented in these models.

**Authors, as per the order of their mention in the paper:**

1. **Javier Ferrando:** Javeir Ferrando is a PhD student researching NLP and AI at the Universitat Politècnica de Catalunya, supervised by Marta R. Costa-jussà. His research focuses on interpretability and analysis of NLP models, with a broader interest in Explainable AI. Here's how to reach him -
**Website:** https://javiferran.github.io/personal/
**LinkedIn:** https://www.linkedin.com/in/javierferrandomonsonis/?originalSubdomain=es
**X:** https://twitter.com/javifer_96
**E-mail ID:** [e-mail]

2. **Gabriele Sarti:** Gabriele Sarti is a PhD student at the Computational Linguistics Group of the University of Groningen and member of the InDeep consortium, working on user-centric interpretability for neural machine translation. He can be reached through -
**Website:** https://gsarti.com/
**LinkedIn:** https://www.linkedin.com/in/gabrielesarti/
**X:** https://www.twitter.com/gsarti_
**E-mail ID:** [e-mail]

3. **Arianna Bisazza:** Arianna Bisazza is an Associate Professor in the Computational Linguistics Group of the University of Groningen. She is passionate about the statistical modeling of human languages, particularly in a multilingual context. Her long-term goal is to design robust language processing algorithms that can adapt to the large variety of linguistic phenomena observed around the world. She can be reached via -
**Website:** https://www.cs.rug.nl/~bisazza/
**LinkedIn:** https://www.linkedin.com/in/arianna-bisazza-92754329/
**X:** https://twitter.com/AriannaBisazza
**E-mail ID:** [e-mail]

4. **Marta R. Costa-jussà:** Marta R. Costa-jussà is a research scientist at Meta AI since February 2022. She received her PhD from the UPC in 2008. Her research experience is mainly in Machine Translation. Here is how one can reach her -
**Website:** https://costa-jussa.com/
**LinkedIn:** https://www.linkedin.com/in/martaruizcostajussa/
**E-mail ID:** [e-mail]

### Paper 9 - [Hallucination of Multimodal Large Language Models: A Survey](https://arxiv.org/pdf/2404.18930)

This paper provides an overview of the recent advances in identifying, evaluating, and mitigating hallucination in multimodal LLMs; it also provides an overview of causes, evaluation benchmarks, metrics, and other strategies to deal with challenges related to detecting hallucinations.

**Authors, as per the order of their mention in the paper:**

1. **Zechen Bai:** Zechen Bai is a PhD student at National University of Singapore, affiliated with Show Lab, supervised by Prof. Mike Shou. His research interests include deep learning and virtual reality, particularly in video understanding, multimodal, and large language models. Here's how he can be reached:
**Website:** https://www.baizechen.site/
**github:** https://github.com/JosephPai
**X:** https://twitter.com/ZechenBai
**E-mail ID:** [e-mail]

2. **Pichao Wang:** Pichao Wang is a Senior Research Scientist at Amazon Prime Video. He received his Ph.D in Computer Science from University of Wollongong, Australia, supervised by Prof. Wanqing Li and Prof. Philip Ogunbona. Here's how one can reach him -
**Website:** https://wangpichao.github.io/
**LinkedIn:** https://www.linkedin.com/in/pichao-wang-494773109/
**E-mail ID:** [e-mail]

3. **Tianjun Xiao:** Tianjun Xiao is Principal Engineer at NVIDIA. He is also a research scientist at the Amazon Web Services AI Lab in Shanghai, China. He can be reached through -
**Website:** https://tianjunxiao.com/
**LinkedIn:** https://www.linkedin.com/in/tianjun-xiao-553a2660/
**github:** https://github.com/sneakerkg
**X:** https://twitter.com/sneakerkg
**E-mail ID:** [e-mail]

4. **Tong He:** Tong He is a a Senior Applied Scientist in AWS Shanghai AI Lab. He has a Master's Degree in Data Mining/Bioinformatics from the Simon Fraser University. He can be reached through -
**Website:** https://hetong007.github.io/
**LinkedIn:** https://www.linkedin.com/in/tong-he-4260b167/
**github:** https://github.com/hetong007
**E-mail ID:** [e-mail]

5. **Zongbo Han:** Zongbo Han is a third-year Ph.D. student at Tianjin University, China. He is also associated with the Show Lab at the National University of Singapore. His research currently focuses on trustworthy artificial intelligence, including fairness and uncertainty in machine learning, trustworthy multimodal fusion and medical artificial intelligence. Here's how he can be reached -
**Website:** https://zongbo-han.github.io/
**github:** https://github.com/hanmenghan
**E-mail ID:** [e-mail]

6. **Zheng Zhang:** Zheng Zhang is the director of the AWS AI Lab in Shanghai. He is also a Professor at the New York University, Shanghai. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/zheng-zhang-54412516/
**github:** https://github.com/zzhang-cn
**E-mail ID:** [e-mail]

7. **Mike Zheng Shou:** Dr. Mike Zheng Shou is a tenure-track Assistant Professor at National University of Singapore and a former Research Scientist at Facebook AI in the Bay Area. He is particularly interested in Multimodal AI video understanding & generation. He can be reached through -
**LinkedIn:** https://www.linkedin.com/in/mike-zheng-shou-09a4a185/
**E-mail ID:** [e-mail]

### Paper 10 - [In-Context Learning with Long-Context Models: An In-Depth Exploration](https://arxiv.org/pdf/2405.00200)

This paper studies the behavior in-context learning of LLMs at extreme context lengths with long-context models; shows that performance increases as hundreds or thousands of demonstrations are used; demonstrates that long-context ICL is less sensitive to random input shuffling than short-context ICL; concludes that the effectiveness of long-context LLMs is not due to task learning but from attending to similar examples.

**Authors, as per the order of their mention in the paper:**

1. **Amanda Bertsch:** a PhD student in the Language Technologies Institute at Carnegie Mellon University, advised by Matt Gormley and Graham Neubig. Her research interests include better ways to reason over large quantities of knowledge, model large-scale structure in text, and effectively integrate external knowledge into models. Here's how one can reach her -
**Website:** https://www.cs.cmu.edu/~abertsch/
**LinkedIn:** https://www.linkedin.com/in/amandabertsch/
**X:** https://twitter.com/abertsch72?lang=en
**E-mail ID:** [e-mail]

2. **Maor Ivgi:** Maor Ivgi is an AI researcher and entrepreneur with experience in implementing state-of-the-art deep learning models for real-world use cases, ranging from computer vision solutions for the energy industry to graph analysis for government law enforcement. He can be reached through -
**Website:** https://mivg.github.io/
**LinkedIn:** https://www.linkedin.com/in/maor-ivgi/
**X:** https://twitter.com/maorivg
**E-mail ID:** [e-mail]

3. **Uri Alon:** Uri Alon is Senior Research Scientist at Google DeepMind. He was previously a post-doctoral researcher at the Carnegie Mellon Institute, working with Prof. Graham Neubig. He can be reached via -
**Website:** https://urialon.ml/
**LinkedIn:** https://www.linkedin.com/in/urialon1/
**E-mail ID:** [e-mail]

4. **Jonathan Berant:** Jonathan Berant is an Associate Professor in the The Blavatnik School of Computer Science at Tel-Aviv University. His field of research is Natural Language Processing. He works on Natural Language Understanding problems such as Semantic Parsing, Question Answering, Paraphrasing, Reading Comprehension, and Textual Entailment. He can be reached through -
**Website:** https://www.cs.tau.ac.il//~joberant/
**LinkedIn:** https://www.linkedin.com/in/jonathan-berant-b80280132/
**Twitter:** https://twitter.com/JonathanBerant
**E-mail ID:** [e-mail]

5. **Matthew R. Gormley:** Is Associate Teaching Professor of Computer Science at the Carnegie Mellon University. His research interests include dialogue summarization, multi-document/long-document summarization, NLP for medical text, multilinguality, low-resource languages and domains, syntactic parsing, semantic parsing, and grammar induction. He can be reached through -
**Website:** https://www.cs.cmu.edu/~mgormley/
**CMU Profile:** https://scholars.cmu.edu/6029-matthew-gormley
**E-mail ID:** [e-mail]

6. **Graham Neubig:** Graham Neubig is an Associate Professor at the Language Technology Institute in the School of Computer Science at the Carnegie Mellon University. His research focuses on machine learning and natural language processing, with a particular focus on question answering, code generation, multilingual processing, and evaluation/interpretability. He can be reached via -
**Website:** https://phontron.com/
**LinkedIn:** https://www.linkedin.com/in/graham-neubig-10b41616b/
**X:** https://www.twitter.com/gneubig
**E-mail ID:** [e-mail]

These were the contributors (and their contact details) to the Top 10 ML Papers of the week as listed on Elvis Saravia's newsletter. Next week, we will be back with another list of contributors. Till then, let us know if you require anything else!

Although no single tool integrates all these tasks, you may achieve them using Scrapy for web scraping, Smtplib for email handling, and a scheduling library like Schedule. Scrapy extracts data from websites, smtplib sends emails, and Schedule automates task execution at set intervals.