Last week, I wrapped up my internship @cohere, where I had the chance to work with fantastic people on RL for LLMs.
It was an amazing 6 months, and I'm excited to share one of the outcomes: ShiQ, a Q-value based RL algorithm for fine-tuning LLMs 🚀
🧵Details in @irombie's post!
I'm excited to share our new pre-print
ShiQ: Bringing back Bellman to LLMs!
arxiv.org/abs/2505.11081
In this work, we propose a new, Q-learning inspired RL algorithm for finetuning LLMs 🎉
(1/n)
🚀 Excited to share the 3rd outcome of my internship at @CohereAI: a new RL algo for agentic LLMs that combines policy learning and world modeling, letting agents verify actions before executing them.
Check out the 🧵 and 📄!
Big thanks to my co-authors and Cohere’s RL team 🙏
📢After months of work, I can finally share our latest research, couldn’t be more thrilled and excited. 🎉
We unify a policy 🤖 and a world model 🌍 into a single LLM, thus no external dynamics model needed!
Why does this matter? Because now, the policy can plan based on its
Excited to share the technical report on Command R7B (7B) and Command A (111B), our flagship model! These models are the result of incredible teamwork at @cohere, and it was an honor to be part of it.
Report: cohere.com/research/paper…
Today (two weeks after model launch 🔥) we're releasing a technical report of how we made Command A and R7B 🚀! It has detailed breakdowns of our training process, and evaluations per capability (tools, multilingual, code, reasoning, safety, enterprise, long context)🧵 1/3.
Still 8 days to submit your work to the ALA workshop at AAMAS! We welcome full papers, work in progress, and 2-page abstracts of recently published journal papers. All the info is available at ala-workshop.github.io.
Excited to announce the 17th Adaptive Learning Agent workshop at @AAMASconf in May! We welcome full papers, work in progress, and 2-page abstracts of recently published journal papers. Find out more at our website: ala-workshop.github.io. Deadline for submissions: February 4th.
