Papers by Xiaoxiao Li

2 papers
For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs (2026.acl-long)

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Challenge: Existing methods for data valuation rely on gradient computations, making them prohibitive for billion-parameter models.
Approach: They propose a forward-only data valuation framework that enables efficient batch-scalable value estimation while maintaining effectiveness.
Outcome: The proposed framework matches or outperforms gradient-based baselines in detecting influential data and mislabeled data while achieving significant efficiency improvements.
CONSTRUCTURE: Benchmarking CONcept STRUCTUre REasoning for Multimodal Large Language Models (2024.findings-emnlp)

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Challenge: Existing multimodal large language models lack the ability to perceive the visual world with a deep concept structure cognition.
Approach: They propose a concept-level benchmark to assess MLLMs’ hierarchical concept understanding and reasoning abilities.
Outcome: The proposed model outperforms state-of-the-art models in concept structure reasoning evaluation.

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