activity
20162024
most citedPerspectives on Large Language Models for Relevance Judgment

170 citations · 981 across the 54 of their papers we have counts for

collaborators

55 papers

cs.IR2024★ 14 cited

Knowledge-Enhanced Conversational Recommendation via Transformer-based Sequential Modelling

Jie Zou, Aixin Sun, Cheng Long +1

In conversational recommender systems (CRSs), conversations usually involve a set of items and item-related entities or attributes, e.g., director is a related entity of a movie. T…

cs.CL2024★ 15 cited

Learning to Ask: Conversational Product Search via Representation Learning

Jie Zou, Jimmy Xiangji Huang, Zhaochun Ren +1

Online shopping platforms, such as Amazon and AliExpress, are increasingly prevalent in society, helping customers purchase products conveniently. With recent progress in natural l…

cs.AI2024

Optimizing Numerical Estimation and Operational Efficiency in the Legal Domain through Large Language Models

Jia-Hong Huang, Chao-Chun Yang, Yixian Shen +2

The legal landscape encompasses a wide array of lawsuit types, presenting lawyers with challenges in delivering timely and accurate information to clients, particularly concerning…

cs.CL2024

Leveraging Graph Structures to Detect Hallucinations in Large Language Models

Noa Nonkes, Sergei Agaronian, Evangelos Kanoulas +1

Large language models are extensively applied across a wide range of tasks, such as customer support, content creation, educational tutoring, and providing financial guidance. Howe…

cs.IR2024★ 1 cited

Towards Fine-Grained Citation Evaluation in Generated Text: A Comparative Analysis of Faithfulness Metrics

Weijia Zhang, Mohammad Aliannejadi, Yifei Yuan +3

Large language models (LLMs) often produce unsupported or unverifiable content, known as "hallucinations." To mitigate this, retrieval-augmented LLMs incorporate citations, groundi…

cs.CL2024★ 6 cited

A Survey on Recent Advances in Conversational Data Generation

Heydar Soudani, Roxana Petcu, Evangelos Kanoulas +1

Recent advancements in conversational systems have significantly enhanced human-machine interactions across various domains. However, training these systems is challenging due to t…