Papers Conversational Search
“Conversational Search” 태그가 달린 논문 154편 · 필터 해제
CTR-Guided Generative Query Suggestion in Conversational Search
Generating effective query suggestions in conversational search requires aligning model outputs with user preferences, which is challenging due to sparse and noisy click signals. We propose GQS, a generative framework th…
Conversational SearchDiversityConversational Search: From Fundamentals to Frontiers in the LLM Era
Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand the users' search intent within the conve…
Conversational SearchInstruction FollowingUnderstanding Mental Models of Generative Conversational Search and The Effect of Interface Transparency
The experience and adoption of conversational search is tied to the accuracy and completeness of users' mental models -- their internal frameworks for understanding and predicting system behaviour. Thus, understanding th…
Conversational SearchConvSearch-R1: Enhancing Query Reformulation for Conversational Search with Reasoning via Reinforcement Learning
Conversational search systems require effective handling of context-dependent queries that often contain ambiguity, omission, and coreference. Conversational Query Reformulation (CQR) addresses this challenge by transfor…
Conversational Searchreinforcement-learningReinforcement LearningRetrievalEfficient Conversational Search via Topical Locality in Dense Retrieval
Pre-trained language models have been widely exploited to learn dense representations of documents and queries for information retrieval. While previous efforts have primarily focused on improving effectiveness and user …
Conversational SearchInformation RetrievalRetrievalSimulating Before Planning: Constructing Intrinsic User World Model for User-Tailored Dialogue Policy Planning
Recent advancements in dialogue policy planning have emphasized optimizing system agent policies to achieve predefined goals, focusing on strategy design, trajectory acquisition, and efficient training paradigms. However…
Active LearningConversational SearchDense Passage Retrieval in Conversational Search
Information retrieval systems have traditionally relied on exact term match methods such as BM25 for first-stage retrieval. However, recent advancements in neural network-based techniques have introduced a new method cal…
Conversational SearchInformation RetrievalOpen-Domain Question AnsweringPassage Retrieval+2Improving the Reusability of Conversational Search Test Collections
Incomplete relevance judgments limit the reusability of test collections. When new systems are compared to previous systems that contributed to the pool, they often face a disadvantage. This is due to pockets of unjudged…
Conversational SearchConversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets
The rise of personalized conversational search systems has been driven by advancements in Large Language Models (LLMs), enabling these systems to retrieve and generate answers for complex information needs. However, the …
Answer GenerationConversational SearchHallucinationRAG+2Zero-Shot and Efficient Clarification Need Prediction in Conversational Search
Clarification need prediction (CNP) is a key task in conversational search, aiming to predict whether to ask a clarifying question or give an answer to the current user query. However, current research on CNP suffers fro…
Conversational SearchcounterfactualA Survey on Multi-Turn Interaction Capabilities of Large Language Models
Multi-turn interaction in the dialogue system research refers to a system's ability to maintain context across multiple dialogue turns, enabling it to generate coherent and contextually relevant responses. Recent advance…
Conversational SearchRALI@TREC iKAT 2024: Achieving Personalization via Retrieval Fusion in Conversational Search
The Recherche Appliquee en Linguistique Informatique (RALI) team participated in the 2024 TREC Interactive Knowledge Assistance (iKAT) Track. In personalized conversational search, effectively capturing a user's complex …
Conversational SearchRetrievalIRLab@iKAT24: Learned Sparse Retrieval with Multi-aspect LLM Query Generation for Conversational Search
The Interactive Knowledge Assistant Track (iKAT) 2024 focuses on advancing conversational assistants, able to adapt their interaction and responses from personalized user knowledge. The track incorporates a Personal Text…
Conversational SearchPassage RankingRerankingResponse Generation+1AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs
Generating diverse and effective clarifying questions is crucial for improving query understanding and retrieval performance in open-domain conversational search (CS) systems. We propose AGENT-CQ (Automatic GENeration, a…
Conversational SearchRetrievalA Survey of Conversational Search
As a cornerstone of modern information access, search engines have become indispensable in everyday life. With the rapid advancements in AI and natural language processing (NLP) technologies, particularly large language …
Conversational SearchInformation RetrievalResponse GenerationRetrieval+1DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Search
Conversational Search (CS) involves retrieving relevant documents from a corpus while considering the conversational context, integrating retrieval with context modeling. Recent advancements in Large Language Models (LLM…
Conversational Information AccessConversational SearchKnowledge DistillationRepresentation Learning+1SAPIENT: Mastering Multi-turn Conversational Recommendation with Strategic Planning and Monte Carlo Tree Search
Conversational Recommender Systems (CRS) proactively engage users in interactive dialogues to elicit user preferences and provide personalized recommendations. Existing methods train Reinforcement Learning (RL)-based age…
Conversational RecommendationConversational SearchRecommendation SystemsReinforcement Learning (RL)Rewriting Conversational Utterances with Instructed Large Language Models
Many recent studies have shown the ability of large language models (LLMs) to achieve state-of-the-art performance on many NLP tasks, such as question answering, text summarization, coding, and translation. In some cases…
Conversational SearchQuestion AnsweringText SummarizationConversational Exploratory Search of Scholarly Publications Using Knowledge Graphs
Traditional search methods primarily depend on string matches, while semantic search targets concept-based matches by recognizing underlying intents and contextual meanings of search terms. Semantic search is particularl…
Conversational SearchKnowledge GraphsTowards Investigating Biases in Spoken Conversational Search
Voice-based systems like Amazon Alexa, Google Assistant, and Apple Siri, along with the growing popularity of OpenAI's ChatGPT and Microsoft's Copilot, serve diverse populations, including visually impaired and low-liter…
Conversational SearchQuestion Answering