Papers by Tongyan Hu

2 papers
FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domain (2025.emnlp-main)

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Challenge: Recent LLMs have demonstrated promising ability in solving finance related problems, but applying them in real-world finance applications remains challenging due to its high risk and high stakes property.
Approach: They propose a benchmark specifically designed for evaluating the trustworthiness of LLMs in finance applications.
Outcome: The proposed benchmark outperforms proprietary models in most tasks while open-source models have advantage in specific areas like industry-level fairness.
VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videos (2025.acl-long)

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Challenge: Multimodal large language models (MLLMs) are used for video quality assessment, image captioning and video analysis.
Approach: They propose a benchmark to evaluate MLLMs on AIGC videos using coherence validation, error awareness, error type detection and reasoning evaluation tasks.
Outcome: The proposed benchmark evaluates 13 frontier MLLMs on AIGC videos.

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