Feng Zhang
Orcid: 0000-0002-8373-9366Affiliations:
- Peking University, Beijing, China
According to our database1,
Feng Zhang
authored at least 20 papers
between 2021 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
ReranKGC: A cooperative retrieve-and-rerank framework for multi-modal knowledge graph completion.
Neural Networks, 2025
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025
Clear Up Confusion: Iterative Differential Generation for Fine-grained Intent Detection with Contrastive Feedback.
Proceedings of the 31st International Conference on Computational Linguistics, 2025
AdaDHP: Fine-Grained Fine-Tuning via Dual Hadamard Product and Adaptive Parameter Selection.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Multi-Label Few-Shot Image Classification via Pairwise Feature Augmentation and Flexible Prompt Learning.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
A Coarse-to-Fine Prototype Learning Approach for Multi-Label Few-Shot Intent Detection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
From Discrimination to Generation: Low-Resource Intent Detection with Language Model Instruction Tuning.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
SELP: A Semantically-Driven Approach for Separated and Accurate Class Prototypes in Few-Shot Text Classification.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
SSPAttack: A Simple and Sweet Paradigm for Black-Box Hard-Label Textual Adversarial Attack.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
2021
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021