most citedTowards Explainable Conversational Recommender Systems

35 citations · 73 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202412 cited

TextMonkey: An OCR-Free Large Multimodal Model for Understanding Document

Yuliang Liu, Biao Yang, Qiang Liu +4

We present TextMonkey, a large multimodal model (LMM) tailored for text-centric tasks. Our approach introduces enhancement across several dimensions: By adopting Shifted Window Att…

cs.CL20231 cited

TempTabQA: Temporal Question Answering for Semi-Structured Tables

Vivek Gupta, Pranshu Kandoi, Mahek Bhavesh Vora +4

Semi-structured data, such as Infobox tables, often include temporal information about entities, either implicitly or explicitly. Can current NLP systems reason about such informat…

cs.IR202335 cited

Towards Explainable Conversational Recommender Systems

Shuyu Guo, Shuo Zhang, Weiwei Sun +3

Explanations in conventional recommender systems have demonstrated benefits in helping the user understand the rationality of the recommendations and improving the system's efficie…

cs.CL2023

Multi-Action Dialog Policy Learning from Logged User Feedback

Shuo Zhang, Junzhou Zhao, Pinghui Wang +5

Multi-action dialog policy, which generates multiple atomic dialog actions per turn, has been widely applied in task-oriented dialog systems to provide expressive and efficient sys…

cs.IR202325 cited

UserSimCRS: A User Simulation Toolkit for Evaluating Conversational Recommender Systems

Jafar Afzali, Aleksander Mark Drzewiecki, Krisztian Balog +1

We present an extensible user simulation toolkit to facilitate automatic evaluation of conversational recommender systems. It builds on an established agenda-based approach and ext…