26 citations · 117 across the 40 of their papers we have counts for
11 papers · 1 filter
Do Images Clarify? A Study on the Effect of Images on Clarifying Questions in Conversational Search
Clemencia Siro, Zahra Abbasiantaeb, Yifei Yuan +2
Conversational search systems increasingly employ clarifying questions to refine user queries and improve the search experience. Previous studies have demonstrated the usefulness o…
Learning to Judge: LLMs Designing and Applying Evaluation Rubrics
Clemencia Siro, Pourya Aliannejadi, Mohammad Aliannejadi
Large language models (LLMs) are increasingly used as evaluators for natural language generation, applying human-defined rubrics to assess system outputs. However, human rubrics ar…
ChatR1: Reinforcement Learning for Conversational Reasoning and Retrieval Augmented Question Answering
Simon Lupart, Mohammad Aliannejadi, Evangelos Kanoulas
We present ChatR1, a reasoning framework based on reinforcement learning (RL) for conversational question answering (CQA). Reasoning plays an important role in CQA, where user inte…
Query Understanding in LLM-based Conversational Information Seeking
Yifei Yuan, Zahra Abbasiantaeb, Yang Deng +1
Query understanding in Conversational Information Seeking (CIS) involves accurately interpreting user intent through context-aware interactions. This includes resolving ambiguities…
PSCon: Product Search Through Conversations
Jie Zou, Mohammad Aliannejadi, Evangelos Kanoulas +5
Conversational Product Search ( CPS ) systems interact with users via natural language to offer personalized and context-aware product lists. However, most existing research on CPS…
AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs
Clemencia Siro, Yifei Yuan, Mohammad Aliannejadi +1
Generating diverse and effective clarifying questions is crucial for improving query understanding and retrieval performance in open-domain conversational search (CS) systems. We p…