Papers by Jingyi Deng

2 papers
DentalGPT: Incentivizing Multimodal Reasoning in Dentistry (2026.findings-acl)

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Challenge: Current multimodal large language models (MLLMs) show limited understanding of dental images.
Approach: They propose a dental-specialized multimodal large language model trained via staged multimodal alignment and reinforcement learning.
Outcome: The proposed model outperforms state-of-the-art models on disease classification and dental VQA tasks.
LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models (2026.acl-long)

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Challenge: Existing evaluation of Large Language Models on static benchmarks is vulnerable to data contamination and leaderboard overfitting.
Approach: LLMEval-Fair framework provides a framework for dynamic evaluation of Large Language Models . evaluators use a proprietary bank of 220k graduate-level questions to analyze model data .
Outcome: LLMEval-Fair provides robust and credible evaluation framework for Large Language Models . it provides a strong empirical validation for the dynamic evaluation paradigm .

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