Pinzheng Wang

According to our database1, Pinzheng Wang authored at least 14 papers between 2023 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Re<sup>2</sup>: Unlocking LLM Reasoning via Reinforcement Learning with Re-solving.
CoRR, March, 2026

2025
OpenBA: an open-sourced 15B bilingual asymmetric Seq2Seq model pre-trained from scratch.
Sci. China Inf. Sci., 2025

Improving Rationality in the Reasoning Process of Language Models through Self-playing Game.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Revealing and Mitigating Over-Attention in Knowledge Editing.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning.
CoRR, 2024

Rethinking Negative Instances for Generative Named Entity Recognition.
CoRR, 2024

Achieving Stronger Generation via Simple Contrastive Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

CMD: a framework for Context-aware Model self-Detoxification.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Rethinking Negative Instances for Generative Named Entity Recognition.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch.
CoRR, 2023

Detoxify Language Model Step-by-Step.
CoRR, 2023

UFNRec: Utilizing False Negative Samples for Sequential Recommendation.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Future Augmentation with Self-distillation in Recommendation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Can Diffusion Model Achieve Better Performance in Text Generation ? Bridging the Gap between Training and Inference !
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023


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