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20172025
most citedTable2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval

95 citations · 665 across the 55 of their papers we have counts for

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60 papers · 1 filter

cs.IR2025

UserSimCRS v2: Simulation-Based Evaluation for Conversational Recommender Systems

Nolwenn Bernard, Krisztian Balog

Resources for simulation-based evaluation of conversational recommender systems (CRSs) are scarce. The UserSimCRS toolkit was introduced to address this gap. In this work, we prese…

cs.IR2025

Sim4IA-Bench: A User Simulation Benchmark Suite for Next Query and Utterance Prediction

Andreas Konstantin Kruff, Christin Katharina Kreutz, Timo Breuer +2

Validating user simulation is a difficult task due to the lack of established measures and benchmarks, which makes it challenging to assess whether a simulator accurately reflects…

cs.IR20253 cited

Limitations of Current Evaluation Practices for Conversational Recommender Systems and the Potential of User Simulation

Nolwenn Bernard, Krisztian Balog

Research and development on conversational recommender systems (CRSs) critically depends on sound and reliable evaluation methodologies. However, the interactive nature of these sy…

cs.IR20251 cited

SimLab: A Platform for Simulation-based Evaluation of Conversational Information Access Systems

Nolwenn Bernard, Sharath Chandra Etagi Suresh, Krisztian Balog +1

Progress in conversational information access (CIA) systems has been hindered by the difficulty of evaluating such systems with reproducible experiments. While user simulation offe…

cs.IR20256 cited

Second SIGIR Workshop on Simulations for Information Access (Sim4IA 2025)

Philipp Schaer, Christin Katharina Kreutz, Krisztian Balog +2

Simulations in information access (IA) have recently gained interest, as shown by various tutorials and workshops around that topic. Simulations can be key contributors to central…

cs.IR202521 cited

Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation

Krisztian Balog, Donald Metzler, Zhen Qin

Large language models (LLMs) are increasingly integral to information retrieval (IR), powering ranking, evaluation, and AI-assisted content creation. This widespread adoption neces…