Shenzhi Wang
Orcid: 0009-0000-0314-4243
According to our database1,
Shenzhi Wang
authored at least 20 papers
between 2014 and 2025.
Collaborative distances:
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Bibliography
2025
CoRR, August, 2025
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning.
CoRR, June, 2025
COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values.
CoRR, April, 2025
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
Hundreds Guide Millions: Adaptive Offline Reinforcement Learning With Expert Guidance.
IEEE Trans. Neural Networks Learn. Syst., November, 2024
DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
CoRR, 2023
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
2021
Glancing at the Patch: Anomaly Localization With Global and Local Feature Comparison.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2014