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20242026
most citedInvestigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models

1 citations · 1 across the 10 of their papers we have counts for

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cs.AI2025

MPR-GUI: Benchmarking and Enhancing Multilingual Perception and Reasoning in GUI Agents

Ruihan Chen, Qiming Li, Xiaocheng Feng +9

Large Vision-Language Models (LVLMs) have shown strong potential as multilingual Graphical User Interface (GUI) agents, as evidenced by existing GUI benchmarks. However, these benc…

cs.CV2025

Causal Tracing of Object Representations in Large Vision Language Models: Mechanistic Interpretability and Hallucination Mitigation

Qiming Li, Zekai Ye, Xiaocheng Feng +3

Despite the remarkable advancements of Large Vision-Language Models (LVLMs), the mechanistic interpretability remains underexplored. Existing analyses are insufficiently comprehens…

cs.CV2025

Unlocking Multilingual Reasoning Capability of LLMs and LVLMs through Representation Engineering

Qiming Li, Xiaocheng Feng, Yixuan Ma +4

Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) demonstrate strong reasoning capabilities, yet their performance in English significantly outperforms that in…

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…