we're looking for a rockstar research eng @haizelabs! if you're interested in training tons of models and thinking about adversarial robustness for real-world deployed AI systems, DM me or apply below :)
What Makes a Base Language Model Suitable for RL?
Rumors in the community say RL (i.e., RLVR) on LLMs is full of “mysteries”:
(1) Is the magic only happening on Qwen + Math?
(2) Does the "aha moment" only spark during math reasoning?
(3) Is evaluation hiding some tricky traps?
Excited to discuss "SFT Memorizes, RL Generalizes" tomorrow at @haizelabs's NYC AI Reading Group with @leonardtang_ and @willccbb! We'll also explore a broader theme — "what does RL actually learn?", guided by some related works from the past week.
We modified DeepSeek's recent Self-Principled Critique Tuning paper and bootstrapped a family of super tiny generalist reward models in < 1 day on a single A100 GPU. By proposing instance-specific rubrics at inference time, j1-micro (1.7B) and j1-nano (0.6B) punch well above
Discussing "Mind the Gap" tonight at @haizelabs's NYC AI Reading Group with @leonardtang_ and @willccbb. Authors study self-improvement through the "Generation-Verification Gap" (model's verification ability over its own generations) and find that this capability log scales with
think it was @jxmnop who said that science is about generating artifacts. inspired me to really focus on this this past week, starting with some internal eng tools and paper summaries... grinding out a couple more researchy things for the next couple weeks :) super excited to
Flying out to #ICML2025 tonight! Always down to chat about unverifiable domains, evals, red-teaming, safeguards, or just meet cool people. I’ll be a panelist at the Methods and Opportunities at Small Scale workshop, sharing our work on tiny generalist reward models
What tools are people using these days to search for relevant citations, e.g., papers that actually benchmark against a particular work? Google Scholar first page is usually surveys/prior work sections, which are somewhat useless for tracing the lineage of an approach
Great discussion tonight at @haizelabs HQ about the many many different definitions of generalization / “out of distribution” and which ones we actually care about in practice.
+ a special shoutout to @marklxu1 for the Joe’s pizza 🤤