Relearn: Machine Unlearning Framework for LLMs
A novel framework for machine unlearning in large language models that enables effective removal of specific knowledge while preserving model performance through a learning-based approach.
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portfolio
Dynamic Correction Decoding for Hallucination Mitigation
A decoding strategy for multimodal large language models that leverages visual information to detect and correct hallucinations during text generation, significantly reducing factual errors.
publications
MLLM Can See? Dynamic Correction Decoding for Hallucination Mitigation
Published in arXiv preprint, 2024
This paper introduces a dynamic correction decoding strategy for multimodal large language models (MLLMs) that leverages visual information to detect and correct hallucinations during text generation, significantly reducing factual errors.
Recommended citation: Xu, H., et al. (2024). "MLLM Can See? Dynamic Correction Decoding for Hallucination Mitigation." arXiv preprint arXiv:2406.00000.
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Relearn: Unlearning via Learning for Large Language Models
Published in arXiv preprint, 2025
This paper introduces Relearn, a novel framework for machine unlearning in large language models that enables effective removal of specific knowledge while preserving model performance through a learning-based approach.
Recommended citation: Xu, H., et al. (2025). "Relearn: Unlearning via Learning for Large Language Models." arXiv preprint arXiv:2408.15168.
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ZJUKLAB at SemEval-2025 Task 4: Unlearning via Model Merging
Published in SemEval-2025, 2025
This paper presents our approach to SemEval-2025 Task 4, which focuses on unlearning in semantic understanding. We propose a model merging strategy that consolidates alternative model versions to enforce effective knowledge removal.
Recommended citation: Xu, H., et al. (2025). "ZJUKLAB at SemEval-2025 Task 4: Unlearning via Model Merging." SemEval-2025.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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