2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Mitigating the Impact of False Negatives in Dense Retrieval with Contrastive Confidence Regularization
Shiqi Wang, Yeqin Zhang, Cam-Tu Nguyen
In open-domain Question Answering (QA), dense retrieval is crucial for finding relevant passages for answer generation. Typically, contrastive learning is used to train a retrieval…
cs.CL2023★ 1 cited
Long Short-Term Planning for Conversational Recommendation Systems
Xian Li, Hongguang Shi, Yunfei Wang +3
In Conversational Recommendation Systems (CRS), the central question is how the conversational agent can naturally ask for user preferences and provide suitable recommendations. Ex…
cs.CL2023★ 2 cited
Coarse-to-Fine Knowledge Selection for Document Grounded Dialogs
Yeqin Zhang, Haomin Fu, Cheng Fu +3
Multi-document grounded dialogue systems (DGDS) belong to a class of conversational agents that answer users' requests by finding supporting knowledge from a collection of document…