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Erxin Yu
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2020 – today
- 2024
- [c7]Erxin Yu, Jing Li, Chunpu Xu:
RePALM: Popular Quote Tweet Generation via Auto-Response Augmentation. ACL (Findings) 2024: 9566-9579 - [c6]Erxin Yu, Jing Li, Chunpu Xu:
PopALM: Popularity-Aligned Language Models for Social Media Trendy Response Prediction. LREC/COLING 2024: 12867-12878 - [i4]Erxin Yu, Jing Li, Chunpu Xu:
PopALM: Popularity-Aligned Language Models for Social Media Trendy Response Prediction. CoRR abs/2402.18950 (2024) - [i3]Erxin Yu, Jing Li, Ming Liao, Siqi Wang, Zuchen Gao, Fei Mi, Lanqing Hong:
CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue Coreference. CoRR abs/2406.17626 (2024) - 2022
- [c5]Erxin Yu, Lan Du, Yuan Jin, Zhepei Wei, Yi Chang:
Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables. EMNLP 2022: 4937-4948 - [c4]Zhepei Wei, Yue Wang, Jinnan Li, Zhining Liu, Erxin Yu, Yuan Tian, Xin Wang, Yi Chang:
Towards Unified Representations of Knowledge Graph and Expert Rules for Machine Learning and Reasoning. AACL/IJCNLP (1) 2022: 240-253 - [i2]Erxin Yu, Lan Du, Yuan Jin, Zhepei Wei, Yi Chang:
Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables. CoRR abs/2211.03616 (2022) - 2021
- [i1]Zhining Liu, Zhepei Wei, Erxin Yu, Qiang Huang, Kai Guo, Boyang Yu, Zhaonian Cai, Hangting Ye, Wei Cao, Jiang Bian, Pengfei Wei, Jing Jiang, Yi Chang:
IMBENS: Ensemble Class-imbalanced Learning in Python. CoRR abs/2111.12776 (2021) - 2020
- [c3]Erxin Yu, Wenjuan Han, Yuan Tian, Yi Chang:
ToHRE: A Top-Down Classification Strategy with Hierarchical Bag Representation for Distantly Supervised Relation Extraction. COLING 2020: 1665-1676 - [c2]Erxin Yu, Yantao Jia, Shang Wang, Fengfu Li, Yi Chang:
Context and Type Enhanced Representation Learning for Relation Extraction. ICKG 2020: 329-335 - [c1]Erxin Yu, Yantao Jia, Yuan Tian, Yi Chang:
A Two-Level Noise-Tolerant Model for Relation Extraction with Reinforcement Learning. ICKG 2020: 367-373
Coauthor Index
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last updated on 2024-09-26 01:01 CEST by the dblp team
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