Papers by Jintong Sun

2 papers
MeMoTune: A Measure and Moment-Driven Fine-Tuning Framework for Quantized Large Language Models (2025.findings-acl)

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Challenge: Existing methods combine quantization with parameter-efficient fine-tuning but fail to meet practical performance requirements.
Approach: They propose a measure and moment approach to optimize objective function for superior fine-tuning results by scaling the update process through a gradient.
Outcome: The proposed framework outperforms state-of-the-art methods on tasks like text generation, summarization, and understanding.
Decoding Scientific Experimental Images: The SPUR Benchmark for Perception, Understanding, and Reasoning (2026.acl-long)

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Challenge: Xu and Peng, 2025) . . SPUR is a comprehensive benchmark for scientific experimental image perception, understanding, and reasoning, comprising 4,264 question-answering (QA) pairs derived from 1,084 expert-curated images.
Approach: They propose to use 4,264 question-answering (QA) pairs derived from 1,084 expert-curated images to evaluate the visual perception of multimodal large language models (MLLMs) . they also propose to utilize cross-panel relation understanding to evaluate MLLM’s ability to decipher intricate cross-panel relations.
Outcome: The proposed model is based on 4,264 question-answering pairs derived from 1,084 expert-curated images.

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