Papers by Fengyuan Sun

2 papers
MisinfoBench: A Multi-Dimensional Benchmark for Evaluating LLMs’ Resilience to Misinformation (2025.findings-emnlp)

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Challenge: Existing benchmarks assess factual accuracy in isolated queries but fail to evaluate LLMs’ resilience to misinformation in interactive settings.
Approach: MisinfoBench is a benchmark designed to assess LLMs’ ability to discern, resist, and reject misinformation.
Outcome: MisinfoBench assesses large language models’ ability to discern, resist, and reject misinformation in interactive settings.
AdaTP: Attention-Debiased Token Pruning for Video Large Language Models (2025.findings-emnlp)

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Challenge: Existing visual token compression methods rely on attention scores but have inherent biases . global and local attention biased scores cause excessive computational overhead .
Approach: They propose a token pruning pipeline that targets global and local attention biases . the pipeline is designed to reduce computational overhead of Video Large Language Models based on visual tokens compiled from multiple video frames .
Outcome: The proposed method significantly reduces the computational overhead of Video Large Language Models while retaining the performance of vanilla models.

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