Papers by Ziyue Lin

2 papers
MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria (2025.naacl-long)

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Challenge: Existing evaluation methodologies for multimodal large language models are limited in evaluating objective queries without considering real-world user experiences.
Approach: They propose to evaluate multimodal large language models with per-sample criteria using potent MLLM as the judge.
Outcome: The proposed evaluation paradigm shows that it can be used to evaluate multimodal large language models with per-sample criteria.
A Survey on Foundation Language Models for Single-cell Biology (2025.acl-long)

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Challenge: Existing single-cell foundation language models are based on pre-trained and large language models.
Approach: They review the development of single-cell foundation language models . they discuss data tokenization strategies and pre-training paradigms .
Outcome: The proposed models have shown remarkable performance in a variety of single-cell data analysis tasks.

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