8 citations · 10 across the 5 of their papers we have counts for
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cs.CL2024
Multi-party Response Generation with Relation Disentanglement
Tianhao Dai, Chengyu Huang, Lizi Liao
Existing neural response generation models have achieved impressive improvements for two-party conversations, which assume that utterances are sequentially organized. However, many…
cs.CL2024★ 1 cited
Training Language Models to Generate Text with Citations via Fine-grained Rewards
Chengyu Huang, Zeqiu Wu, Yushi Hu +1
While recent Large Language Models (LLMs) have proven useful in answering user queries, they are prone to hallucination, and their responses often lack credibility due to missing r…
cs.CL2022
Conversation Disentanglement with Bi-Level Contrastive Learning
Chengyu Huang, Zheng Zhang, Hao Fei +1
Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main dr…