From the 1 of 6 linked papers with an AI index.
6 papers
CARE: Confidence-Aware Reasoning for Reliable Medical VQA
Yuetian Du, Yucheng Wang, Zhenyuan Chen +9
Reinforcement Fine-Tuning (RFT) has enabled medical Multimodal Large Language Models (MLLMs) to produce Chain-of-Thought (CoT) reasoning for visual question answering, yet these mo…
Living-Harness Is an Interactive-Agent Evolver
Yuetian Du, Yucheng Wang, He Xu +9
The paper introduces Living-Harness, a self‑evolving harness for large language model agents that updates procedural knowledge from episode feedback, enabling the agent to avoid re…
Confidence Calibration for Multimodal LLMs: An Empirical Study through Medical VQA
Yuetian Du, Yucheng Wang, Ming Kong +4
Multimodal Large Language Models (MLLMs) show great potential in medical tasks, but their elicited confidence often misaligns with actual accuracy, potentially leading to misdiagno…
G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition
Jing Peng, Ziyi Chen, Haoyu Li +7
We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting, chunk-wise inference must preserve me…
Linking Perception, Confidence and Accuracy in MLLMs
Yuetian Du, Yucheng Wang, Rongyu Zhang +5
Recent advances in Multi-modal Large Language Models (MLLMs) have predominantly focused on enhancing visual perception to improve accuracy. However, a critical question remains une…
Unmasking Reasoning Processes: A Process-aware Benchmark for Evaluating Structural Mathematical Reasoning in LLMs
Xiang Zheng, Weiqi Zhai, Wei Wang +15
Recent large language models (LLMs) achieve near-saturation accuracy on many established mathematical reasoning benchmarks, raising concerns about their ability to diagnose genuine…