Changze Lv

According to our database1, Changze Lv authored at least 14 papers between 2023 and 2025.

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

Timeline

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Links

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Bibliography

2025
Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024
Multi-Programming Language Sandbox for LLMs.
CoRR, 2024

Towards Biologically Plausible Computing: A Comprehensive Comparison.
CoRR, 2024

Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators.
CoRR, 2024

Decoding Continuous Character-based Language from Non-invasive Brain Recordings.
CoRR, 2024

Efficient and Effective Time-Series Forecasting with Spiking Neural Networks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Promoting Data and Model Privacy in Federated Learning through Quantized LoRA.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Searching for Best Practices in Retrieval-Augmented Generation.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Advancing Parameter Efficiency in Fine-tuning via Representation Editing.
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.
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.
CoRR, 2023

SpikeBERT: A Language Spikformer Trained with Two-Stage Knowledge Distillation from BERT.
CoRR, 2023

Spiking Convolutional Neural Networks for Text Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Parameter Efficient Multi-task Fine-tuning by Learning to Transfer Token-wise Prompts.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023


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