collaborators

5 papers

cs.CV2026

MLLMs Get It Right, Then Get It Wrong: Tracing and Correcting Late-Layer Textual Bias

Xingming Li, Ao Cheng, Qiyao Sun +4

When vision contradicts text, multimodal large language models (MLLMs) consistently favor text, even when images provide clear evidence otherwise. This bias poses risks for applica…

cs.LG2026

Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation

Xixiang He, Qiyao Sun, Ao Cheng +5

Group Relative Policy Optimization (GRPO), a prominent algorithm within the Reinforcement Learning from Verifiable Rewards (RLVR) framework, has achieved strong results in improvin…

cs.CL2026

When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools

Xingming Li, Runke Huang, Yanan Bao +3

High-quality teacher-child interaction (TCI) is fundamental to early childhood development, yet traditional expert-based assessment faces a critical scalability challenge. In large…

cs.CL2026

Efficient Hallucination Detection: Adaptive Bayesian Estimation of Semantic Entropy with Guided Semantic Exploration

Qiyao Sun, Xingming Li, Xixiang He +5

Large language models (LLMs) have achieved remarkable success in various natural language processing tasks, yet they remain prone to generating factually incorrect outputs known as…

cs.CV2026

ENC-Bench: A Benchmark for Evaluating Multimodal Large Language Models in Electronic Navigational Chart Understanding

Ao Cheng, Xingming Li, Xuanyu Ji +5

Electronic Navigational Charts (ENCs) are the safety-critical backbone of modern maritime navigation, yet it remains unclear whether multimodal large language models (MLLMs) can re…