Devin White
@DevinWhiteAI
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ML Researcher @USAEOP. Pushing RLHF forward & using LLMs to master gameplay.
Joined February 2024
Thank you to everyone who stopped by our presentations yesterday! I had a great time sharing our work and chatting with so many of you.
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If you're at #ICML2025 🇨🇦, join us today for our "Too Big to Think" oral presentation at 9:30AM (Room 215-216) and "Multi-Task Reward Learning from Human Ratings" poster at 12PM (Ballroom A)! See you there! #TinyTitans #RLHF.
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RT @SciFi: Multi-Task Reward Learning from Human Ratings.
arxiv.org
Reinforcement learning from human feedback (RLHF) has become a key factor in aligning model behavior with users' goals. However, while humans integrate multiple strategies when making decisions,...
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RT @rohanpaul_ai: Paper - Paper Title: "Too Big to Think: Capacity, Memorization, and Generalization in Pre-Traine….
arxiv.org
The relationship between memorization and generalization in large language models (LLMs) remains an open area of research, with growing evidence that the two are deeply intertwined. In this work,...
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Big news! 🎉 Our paper “Multi-Task Reward Learning from Human Ratings” was accepted to the Models of Human Feedback for AI Alignment workshop at #ICML2025!. In this paper we treat ratings not just as class labels, but as rich reward signals with underlying structure and scale.
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🚨Exciting news!🚨.Our paper, “Too Big to Think: Capacity, Memorization, and Generalization in Pre-Trained Transformers”, was accepted for an oral presentation at the Tiny Titans: The next wave of On-Device Learning for Foundational Models workshop (@tinytitans_icml) at.
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🚨 Big news! Simple RbRL now has a sleek, user-friendly interface! 🖥️✨. You can now:.✅ Rate trajectories directly in the UI.✅ Train RL agents with human feedback.✅ Explore Rating-based RL hands-on with ease. This lightweight, open-source tool makes RbRL accessible to.
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RT @rowancheung: OpenAI just dropped a GitHub connector for ChatGPT’s Deep Research. Now you can plug into GitHub repos to search code, sca….
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🚀 Big update to Atari-GPT!. ✨ Progress bar during testing (steps & reward) .✨ Cleaner function definitions for ease of use .✨ Easy game/model selection via CLI .✨ New analysis file to visualize results . Perfect for Atari AI fans! Try it out and share your results!.
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Check out all the things we have been working on here:
scholar.google.com
Machine Learning Researcher, Army Educational Outreach Program - Cited by 40 - RLHF - Human Guided Reinforcement Learning - AI Alignment - Large Language Models - Small Language Model
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🎉I’m excited to say that I have reached a small but personal milestone of 20 citations! . I want to say a huge thank you to everyone who I have had the honor of collaborating with and I'm excited for what's next!
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Learning from Negative Feedback, Positive Feedback, or Both: RbRL2.0: Integrated Reward and Policy Learning for Rating-based Reinforcement Learning:
arxiv.org
Reinforcement learning (RL), a common tool in decision making, learns policies from various experiences based on the associated cumulative return/rewards without treating them differently. On the...
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RT @ManlingLi_: Today is the day! Welcome to our 2nd workshop on Knowledgeable Foundation Models in Room 112. Come and talk with these won….
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Curious how Atari-GPT blends Atari's retro feel with advanced LLMs? Discover the magic here:
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Exciting update on my Simple RLHF codebase! New results replicate the original RbRL paper, but cut training time by ~33% and run smoothly on modern hardware (like M-series Apple Silicon). Curious? Dive into the details here: #RLHF #AI #MachineLearning
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