8 papers
Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning
Changwei Yao, Xinzi Liu, Chen Li +1
Designing effective reward functions remains a major challenge in reinforcement learning (RL), often requiring considerable human expertise and iterative refinement. Recent advance…
Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners
Qingyang Liu, Bingjie Gao, Canmiao Fu +9
Recent unified models integrate multimodal understanding and generation within a single framework. However, an "understanding-generation gap" persists, where models can capture use…
When to Re-Commit: Temporal Abstraction Discovery for Long-Horizon Vision-Language Reasoning
Chen Li, Zhantao Yang, Fangyi Chen +3
Long-horizon reasoning requires deciding not only what actions to take, but how deeply to commit before the next observation. We formalize this as \emph{commitment depth}: the numb…
ORCE: Order-Aware Alignment of Verbalized Confidence in Large Language Models
Chen Li, Xiaoling Hu, Songzhu Zheng +2
Large language models (LLMs) often produce answers with high certainty even when they are incorrect, making reliable confidence estimation essential for deployment in real-world sc…
Improving Temporal Action Segmentation via Constraint-Aware Decoding
Yeo Keat Ee, Debaditya Roy, Chen Li +2
Temporal action segmentation (TAS) divides untrimmed videos into labeled action segments. While fully supervised methods have advanced the field, challenges such as action variabil…
STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision
Chen Li, Han Zhang, Zhantao Yang +4
Vision-language models (VLMs) have made significant strides in reasoning, yet they often struggle with complex multimodal tasks and tend to generate overly verbose outputs. A key l…