collaborators

7 papers

cs.CV2026

CAST: Mitigating Object Hallucination in Large Vision-Language Models via Caption-Guided Visual Attention Steering

Qiming Li, Zekai Ye, Xiaocheng Feng +9

Although Large Vision-Language Models (LVLMs) have demonstrated remarkable performance on downstream tasks, they frequently produce contents that deviate from visual information, l…

cs.AI2026

SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution

Xiachong Feng, Yi Jiang, Xiaocheng Feng +9

Social intelligence, the ability to navigate complex interpersonal interactions, presents a fundamental challenge for language agents. Training such agents via reinforcement learni…

cs.AI2026

Stratagem: Learning Transferable Reasoning via Trajectory-Modulated Game Self-Play

Xiachong Feng, Deyi Yin, Xiaocheng Feng +9

Games offer a compelling paradigm for developing general reasoning capabilities in language models, as they naturally demand strategic planning, probabilistic inference, and adapti…

cs.CL2026

Exploring Cross-lingual Latent Transplantation: Mutual Opportunities and Open Challenges

Yangfan Ye, Xiaocheng Feng, Xiachong Feng +11

Current large language models (LLMs) often exhibit imbalances in multilingual capabilities and cultural adaptability, largely attributed to their English-centric pre-training data.…

cs.CV2025

CAI: Caption-Sensitive Attention Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Qiming Li, Zekai Ye, Xiaocheng Feng +8

Although Large Vision-Language Models (LVLMs) have demonstrated powerful capabilities in interpreting visual information, they frequently produce content that deviates from visual…

cs.CL2025

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention

Zekai Ye, Qiming Li, Xiaocheng Feng +10

Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal abilities but remain prone to multilingual object hallucination, with a higher likelihood of generating…