Muling Wu

According to our database¹, Muling Wu authored at least 19 papers between 2023 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2025

Structural Reward Model: Enhancing Interpretability, Efficiency, and Scalability in Reward Modeling.

[BibT_eX]

[DOI]

CoRR, September, 2025

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization.

[BibT_eX]

[DOI]

CoRR, August, 2025

Progressive Mastery: Customized Curriculum Learning with Guided Prompting for Mathematical Reasoning.

[BibT_eX]

[DOI]

CoRR, June, 2025

RECAST: Strengthening LLMs' Complex Instruction Following with Constraint-Verifiable Data.

[BibT_eX]

[DOI]

CoRR, May, 2025

Improving RL Exploration for LLM Reasoning through Retrospective Replay.

[BibT_eX]

[DOI]

CoRR, April, 2025

SpikeCLIP: A contrastive language-image pretrained spiking neural network.

[BibT_eX]

[DOI]

Neural Networks, 2025

Improving RL Exploration for LLM Reasoning Through Retrospective Replay.

[BibT_eX]

[DOI]

Proceedings of the Natural Language Processing and Chinese Computing, 2025

Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective.

[BibT_eX]

[DOI]

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Tell Me What You Don't Know: Enhancing Refusal Capabilities of Role-Playing Agents via Representation Space Analysis and Editing.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Multi-Programming Language Sandbox for LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

Tell Me What You Don't Know: Enhancing Refusal Capabilities of Role-Playing Agents via Representation Space Analysis and Editing.

[BibT_eX]

[DOI]

CoRR, 2024

What's Wrong with Your Code Generated by Large Language Models? An Extensive Study.

[BibT_eX]

[DOI]

CoRR, 2024

Towards Biologically Plausible Computing: A Comprehensive Comparison.

[BibT_eX]

[DOI]

CoRR, 2024

Promoting Data and Model Privacy in Federated Learning through Quantized LoRA.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Advancing Parameter Efficiency in Fine-tuning via Representation Editing.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Aligning Large Language Models with Human Preferences through Representation Engineering.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network.

[BibT_eX]

[DOI]

CoRR, 2023

Parameter Efficient Multi-task Fine-tuning by Learning to Transfer Token-wise Prompts.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Watermarking PLMs on Classification Tasks by Combining Contrastive Learning with Weight Perturbation.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Muling Wu

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