4 papers
Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents
Reuben Tan, Baolin Peng, Zhengyuan Yang +16
Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally optimized using sparse, outcome-bas…
Exploration and Exploitation Errors Are Measurable for Language Model Agents
Jaden Park, Jungtaek Kim, Jongwon Jeong +3
Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding to physical AI. A core requirement in these settings is the ability to…
Spatially Grounded Long-Horizon Task Planning in the Wild
Sehun Jung, HyunJee Song, Dong-Hee Kim +4
Recent advances in robot manipulation increasingly leverage Vision-Language Models (VLMs) for high-level reasoning, such as decomposing task instructions into sequential action pla…
VideoWeave: A Data-Centric Approach for Efficient Video Understanding
Zane Durante, Silky Singh, Arpandeep Khatua +6
Training video-language models is often prohibitively expensive due to the high cost of processing long frame sequences and the limited availability of annotated long videos. We pr…