5 papers
What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
Yan Ma, Weiyu Zhang, Tianle Li +3
Vision tool-use reinforcement learning (RL) can equip vision language models with visual operators such as crop-and-zoom and achieves strong performance gains, yet it remains uncle…
Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols
Xianchao Zeng, Xinyu Zhou, Youcheng Li +5
Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic manipulation, yet they remain limited in failure diagnosis and learning from failures. Add…
Project MPG: towards a generalized performance benchmark for LLM capabilities
Lucas Spangher, Tianle Li, William F. Arnold +6
There exists an extremely wide array of LLM benchmarking tasks, whereas oftentimes a single number is the most actionable for decision-making, especially by non-experts. No such ag…
Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development
Tengfei Ma, Xuan Lin, Tianle Li +8
Large Language Models (LLMs) have recently demonstrated remarkable performance in general tasks across various fields. However, their effectiveness within specific domains such as…
SWAG: Storytelling With Action Guidance
Zeeshan Patel, Karim El-Refai, Jonathan Pei +1
Automated long-form story generation typically employs long-context large language models (LLMs) for one-shot creation, which can produce cohesive but not necessarily engaging cont…