4 papers
Do multimodal models imagine electric sheep?
Santhosh Kumar Ramakrishnan, Carl Vondrick, Raja Giryes +2
Yes. We find that large multimodal models develop mental imagery when solving spatial puzzles, and they do imagine sheep when solving sheep puzzles. We fine-tune a Qwen3.5 VLM to s…
Entropy-Preserving Reinforcement Learning
Aleksei Petrenko, Ben Lipkin, Kevin Chen +4
Policy gradient algorithms have driven many recent advancements in language model reasoning. An appealing property is their ability to learn from exploration on their own trajector…
Reinforcement Learning for Long-Horizon Interactive LLM Agents
Kevin Chen, Marco Cusumano-Towner, Brody Huval +4
Interactive digital agents (IDAs) leverage APIs of stateful digital environments to perform tasks in response to user requests. While IDAs powered by instruction-tuned large langua…
Robust Autonomy Emerges from Self-Play
Marco Cusumano-Towner, David Hafner, Alex Hertzberg +9
Self-play has powered breakthroughs in two-player and multi-player games. Here we show that self-play is a surprisingly effective strategy in another domain. We show that robust an…