Edward Beeching

Timeline

1. 2020–2022

   A PhD in embodied learning

   At INSA Lyon with INRIA's CHROMA team, he studies deep reinforcement learning for planning, navigation, and embodied agents and completes a PhD at Université de Lyon in 2022. His 2020 ECCV paper trains a navigation agent with a learned planner over uncertain topological maps; his doctoral work develops EgoMap, a structured neural memory architecture for deep reinforcement learning.

2. March 2022

   Decision Transformers at Hugging Face

   He and Thomas Simonini integrate the Decision Transformer, an offline reinforcement-learning method, into Hugging Face's Transformers library and Hub in March 2022. Their guide describes the model as a conditional sequence learner that predicts actions from a target return, past states, and actions.

3. April 2023

   StackLLaMA and RLHF

   In April 2023, he coauthors StackLLaMA, a guide to train LLaMA for Stack Exchange question answering with reinforcement learning from human feedback. Hugging Face releases the model and its training pipeline through the TRL library.

4. October 2023

   Zephyr and direct alignment

   In October 2023, he coauthors Zephyr: Direct Distillation of LM Alignment. The method trains a chat model from teacher-ranked outputs with distilled direct preference optimization, and the paper reports state-of-the-art results for 7B chat models without human annotation.

5. July 2024

   NuminaMath wins the AIMO prize

   In early 2024, the Numina team adds Beeching and Lewis Tunstall, two Hugging Face fine-tuning experts, for the AI Math Olympiad Progress Prize. NuminaMath 7B TIR wins the first progress prize in July 2024, solving 29 of 50 private test problems.

6. February 2025

   Open-R1's reasoning pipeline

   In February 2025, he coauthors Hugging Face's Open-R1 update, which sets out to reproduce DeepSeek-R1's training pipeline and synthetic data.

7. As of October 2026

   Research scientist at Hugging Face

   He is a Machine Learning Research Scientist at Hugging Face, focused on reinforcement learning and post-training for language models, open reasoning systems, and efficient training infrastructure. In May 2026, he coauthors Delta Weight Sync in TRL, a sparse update method that sends changed model weights through a Hugging Face Bucket to vLLM for asynchronous reinforcement-learning training.