2 citations · 7 across the 6 of their papers we have counts for
6 papers
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…
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…
Improving Question Generation with Multi-level Content Planning
Zehua Xia, Qi Gou, Bowen Yu +4
This paper addresses the problem of generating questions from a given context and an answer, specifically focusing on questions that require multi-hop reasoning across an extended…
Revisiting the Role of Similarity and Dissimilarity in Best Counter Argument Retrieval
Hongguang Shi, Shuirong Cao, Cam-Tu Nguyen
This paper studies the task of best counter-argument retrieval given an input argument. Following the definition that the best counter-argument addresses the same aspects as the in…
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…
Doc2Bot: Accessing Heterogeneous Documents via Conversational Bots
Haomin Fu, Yeqin Zhang, Haiyang Yu +5
This paper introduces Doc2Bot, a novel dataset for building machines that help users seek information via conversations. This is of particular interest for companies and organizati…