Han Wu

Orcid: 0000-0002-8008-064X

Affiliations:
  • City University of Hong Kong Shenzhen Research Institute


According to our database1, Han Wu authored at least 27 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions.
CoRR, August, 2025

Activation-Guided Consensus Merging for Large Language Models.
CoRR, May, 2025

Beyond Standard MoE: Mixture of Latent Experts for Resource-Efficient Language Models.
CoRR, March, 2025

Unlocking Efficient Long-to-Short LLM Reasoning with Model Merging.
CoRR, March, 2025

LoRE-Merging: Exploring Low-Rank Estimation For Large Language Model Merging.
CoRR, February, 2025

1bit-Merging: Dynamic Quantized Merging for Large Language Models.
CoRR, February, 2025

OPTISHEAR: Towards Efficient and Adaptive Pruning of Large Language Models via Evolutionary Optimization.
CoRR, February, 2025

Towards Improving Interpretability of Language Model Generation Through a Structured Knowledge Discovery Approach.
IEEE J. Sel. Top. Signal Process., January, 2025

Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

BPP-Search: Enhancing Tree of Thought Reasoning for Mathematical Modeling Problem Solving.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Sens-Merging: Sensitivity-Guided Parameter Balancing for Merging Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Structure-Aware Dialogue Modeling Methods for Conversational Semantic Role Labeling.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

BPP-Search: Enhancing Tree of Thought Reasoning for Mathematical Modeling Problem Solving.
CoRR, 2024

Learning From Correctness Without Prompting Makes LLM Efficient Reasoner.
CoRR, 2024

2023
Self-Supervised Sentence Compression for Meeting Summarization.
CoRR, 2023

Towards Versatile and Efficient Visual Knowledge Injection into Pre-trained Language Models with Cross-Modal Adapters.
CoRR, 2023

Learning Locality and Isotropy in Dialogue Modeling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Fine-grained Conversational Decoding via Isotropic and Proximal Search.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

VCSUM: A Versatile Chinese Meeting Summarization Dataset.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Zero-shot Cross-lingual Conversational Semantic Role Labeling.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

A Sentence is Worth 128 Pseudo Tokens: A Semantic-Aware Contrastive Learning Framework for Sentence Embeddings.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
Conversational Semantic Role Labeling.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

K-CSRL: Knowledge Enhanced Conversational Semantic Role Labeling.
Proceedings of the ICMLC 2021: 13th International Conference on Machine Learning and Computing, 2021

CSAGN: Conversational Structure Aware Graph Network for Conversational Semantic Role Labeling.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Domain-Adaptive Pretraining Methods for Dialogue Understanding.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Semantic Role Labeling Guided Multi-turn Dialogue ReWriter.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020


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