Olmo 3.1: even more RL = even more RL-Zero! @saurabhshah2.bsky.social and I tweaked some hyperparams and prompts, @hamishivi.bsky.social and @finbarr.bsky.social improved the code and boom! New Olmo 3.1 RL-Zero 👾 An updated, solid baseline for your RL and reasoning research

Nathan Lambert@natolambert.bsky.social · 8mo ago

Olmo 3.1 32B Think shows that not just frontier labs can scale RL. My favorite RL run yet over 7+ years of doing RL. The biggest fully open RL run ever? Gold stars on downstream evals is our original release, this latest one is the final checkpoint on the plot.

Check out Olmo 3 RL-Zero: a clean and scientific setup to benchmark RLVR Everyone is finetuning with Qwen but its hard to know whether your eval is contaminated and skewing your RLVR results. Olmo 3 has a solution.

Nathan Lambert@natolambert.bsky.social · 9mo ago

We present Olmo 3, our next family of fully open, leading language models. This family of 7B and 32B models represents: 1. The best 32B base model. 2. The best 7B Western thinking & instruct models. 3. The first 32B (or larger) fully open reasoning model.

We present Olmo 3, our next family of fully open, leading language models. This family of 7B and 32B models represents: 1. The best 32B base model. 2. The best 7B Western thinking & instruct models. 3. The first 32B (or larger) fully open reasoning model.

Preprint Alert 🚀 Multi-agent reinforcement learning (MARL) often assumes that agents know when other agents cooperate with them. But for humans, this isn’t always the case. For example, plains indigenous groups used to leave resources for others to use at effigies called Manitokan. 1/8

@dnllvy.bsky.social @oumarkaba.bsky.social presenting cool work at #ICLR2025 on generative models for crystals leveraging symmetry ❄️🪞, repping @mila-quebec.bsky.social

Models like DeepSeek-R1 🐋 mark a fundamental shift in how LLMs approach complex problems. In our preprint on R1 Thoughtology, we study R1’s reasoning chains across a variety of tasks; investigating its capabilities, limitations, and behaviour. 🔗: mcgill-nlp.github.io/thoughtology/

Llama 4 uses async RLHF and I would just like to announce that I called it t.co/w9qJxr944C

Our work on Asynchronous RLHF was accepted to #ICLR2025 ! (I was so excited to announce it, I forgot to say I was excited) Used by @ai2.bsky.social for OLMo-2 32B 🔥 New results show ~70% speedups for LLM + RL math and reasoning 🧠 🧵below or hear my DLCT talk online on March 28!

Programming using an AI assistant in order to improve AI assistants is giving me strong sci-fi vibes. Specifically Isaac Asimov, who clearly invented vibe coding in 1956 users.ece.cmu.edu/~gamvrosi/th...

I'm at #NeurIPS2024 this week if anyone wants to talk about RLHF while drinking an overpriced (but excellent) pourover coffee or tea!