# Jason Weston
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jason weston (born 11 January 1971 in Portsmouth) is an English former professional snooker player. He competed on the main tour between 1991 and 1997 and intermittently until 2003, at one point being ranked the world number 90.
After successfully entering Q School in 2015, Weston regained his professional status for the 2015–16 season after a twelve-year absence.
arxiv preprint - Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources
In this episode, we discuss Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources by Alisia Lupidi, Carlos Gemmell, Nicola Cancedda, Jane Dwivedi-Yu, Jason Weston, Jakob Foerster, Roberta Raileanu, Maria Lomeli. The paper presents Source2Synth, a method designed to enha…
arxiv preprint - Thinking LLMs: General Instruction Following with Thought Generation
In this episode, we discuss Thinking LLMs: General Instruction Following with Thought Generation by Tianhao Wu, Janice Lan, Weizhe Yuan, Jiantao Jiao, Jason Weston, Sainbayar Sukhbaatar. The paper introduces a novel approach to enhance Large Language Models by incorporating an iterative thought pro…
MICROSOFT LAUNCHES AI AGENTS
Plus Can AI Really Train AI? ▶️Meta's "Self-Taught Evaluator" trains and evaluates AIs autonomously, using the "chain of thought" method to boost accuracy, potentially outperforming human feedback.
Microsoft Announces New Generative AI Agents for Businesses
Microsoft has unveiled a series of se…
Self-Consistency Preference Optimization
🤗 Paper Upvotes: 5 | cs.CL, cs.AI, cs.LG
Authors:
Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang, Jing Xu, Maryam Fazel-Zarandi, Mohit Bansal, Sainbayar Sukhbaatar, Jason Weston, Jane Yu
Title:
Self-Consistency Preference Optimization
…
Understanding the Coconut Method: Enhancing AI Reasoning with a Continuous Latent Space Approach
This episode analyzes the research paper "Training Large Language Models to Reason in a Continuous Latent Space" by Shibo Hao, Sainbayar Sukhbaatar, DiJia Su, Xian Li, Zhiting Hu, Jason Weston, and Yuandong Tian from FAIR at Meta and UC San Diego. It explores the limitations of traditional chain-of…
Training Large Language Models to Reason in a Continuous Latent Space
🤗 Upvotes: 25 | cs.CL
Authors:
Shibo Hao, Sainbayar Sukhbaatar, DiJia Su, Xian Li, Zhiting Hu, Jason Weston, Yuandong Tian
Title:
Training Large Language Models to Reason in a Continuous Latent Space
Arxiv:
http://arxiv.o…
Exploring FAIR at Meta’s Byte Latent Transformer: Enhancing AI Efficiency with Byte Patches
This episode analyzes the research paper titled **"Byte Latent Transformer: Patches Scale Better Than Tokens,"** authored by Artidoro Pagnoni, Ram Pasunuru, Pedro Rodriguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, A…
Arxiv paper - Byte Latent Transformer: Patches Scale Better Than Tokens
In this episode, we discuss Byte Latent Transformer: Patches Scale Better Than Tokens by Artidoro Pagnoni, Ram Pasunuru, Pedro Rodriguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Ari Holtzman, Srinivasan Iyer. The By…
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback
🤗 Upvotes: 7 | cs.LG, cs.AI
Authors:
Yen-Ting Lin, Di Jin, Tengyu Xu, Tianhao Wu, Sainbayar Sukhbaatar, Chen Zhu, Yun He, Yun-Nung Chen, Jason Weston, Yuandong Tian, Arash Rahnama, Sinong Wang, Hao Ma, Han Fang
Title:
Step-KTO: Optimizing Mathemat…
Self-Rewarding Language Models
In this episode, we discuss Self-Rewarding Language Models by Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, Jason Weston. The paper proposes training language models to give themselves feedback using a self-rewarding approach, bypassing the limitations of…
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