Papers by Xinhao Xu

2 papers
Mitigating Hallucinations in Multi-modal Large Language Models via Image Token Attention-Guided Decoding (2025.naacl-long)

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Challenge: Multi-modal large language models (MLLMs) generate plausible but incorrect content, resulting in hallucinations . recent advances in MLLM technology have demonstrated their outstanding performance in a variety of visual tasks, such as object detection.
Approach: They propose a plug-and-play method which leverages MLLMs’ internal representations to mitigate hallucinations by analyzing input and output tokens.
Outcome: The proposed method exploits MLLMs’ internal representations to mitigate hallucinations.
Extending LLM Context Window with Adaptive Grouped Positional Encoding: A Training-Free Method (2025.acl-long)

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Challenge: Existing long-context training data is scarce and requires substantial GPU resources for training.
Approach: They propose a training-free plug-and-play method to enhance long-context understanding in existing large language models.
Outcome: The proposed method outperforms existing LLMs on various tasks and surpasses baseline methods.

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