Buchumschlag

Sherlock Your Queries: Learning to Ask the Right Questions for Dialogue-Based Retrieval

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Yun, Dong, Schouten, Marco, Papadopoulos, Dim
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Artificial Intelligence
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questions
von: Testoni, Alberto, et al.
Veröffentlicht: (2024)

First Ask Then Answer: A Framework Design for AI Dialogue Based on Supplementary Questioning with Large Language Models
von: Fu, Chuanruo, et al.
Veröffentlicht: (2025)

IntelliAsk: Learning to Ask High-Quality Research Questions via RLVR
von: Sharma, Karun, et al.
Veröffentlicht: (2026)

CLARINET: Augmenting Language Models to Ask Clarification Questions for Retrieval
von: Chi, Yizhou, et al.
Veröffentlicht: (2024)

Can LLMs Ask Good Questions?
von: Zhang, Yueheng, et al.
Veröffentlicht: (2025)

Ask Good Questions for Large Language Models
von: Wu, Qi, et al.
Veröffentlicht: (2025)

From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?
von: Zhou, Zhanke, et al.
Veröffentlicht: (2025)

Teaching LLMs to Ask: Self-Querying Category-Theoretic Planning for Under-Specified Reasoning
von: Qu, Shuhui
Veröffentlicht: (2026)

Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering
von: Czyżnikiewicz, Mateusz, et al.
Veröffentlicht: (2026)

Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction
von: Liu, Tong, et al.
Veröffentlicht: (2024)

MAD-Sherlock: Multi-Agent Debate for Visual Misinformation Detection
von: Lakara, Kumud, et al.
Veröffentlicht: (2024)

HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues
von: Zhong, Yijie, et al.
Veröffentlicht: (2026)

STaR-GATE: Teaching Language Models to Ask Clarifying Questions
von: Andukuri, Chinmaya, et al.
Veröffentlicht: (2024)

AgentAsk: Multi-Agent Systems Need to Ask
von: Lin, Bohan, et al.
Veröffentlicht: (2025)

Ask and Remember: A Questions-Only Replay Strategy for Continual Visual Question Answering
von: Marouf, Imad Eddine, et al.
Veröffentlicht: (2025)

AskNearby: An LLM-Based Application for Neighborhood Information Retrieval and Personalized Cognitive-Map Recommendations
von: Niu, Luyao, et al.
Veröffentlicht: (2025)

UniRQR: A Unified Model for Retrieval Decision, Query, and Response Generation in Internet-Based Knowledge Dialogue Systems
von: Hu, Zhongtian, et al.
Veröffentlicht: (2024)

MGRetrieval: Memory-Guided Reflective Retrieval for Long-Term Dialogue Agents
von: Wang, Tan, et al.
Veröffentlicht: (2026)

Are We Asking the Right Questions? On Ambiguity in Natural Language Queries for Tabular Data Analysis
von: Gomm, Daniel, et al.
Veröffentlicht: (2025)

JEDA: Query-Free Clinical Order Search from Ambient Dialogues
von: Singh, Praphul, et al.
Veröffentlicht: (2025)

DecomposeRL: Learning to Ask Useful, Informative, and Diverse Questions for Semi-Supervised, Traceable Claim Verification
von: Dipta, Shubhashis Roy, et al.
Veröffentlicht: (2026)

Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models
von: Yan, Xue, et al.
Veröffentlicht: (2023)

Learning Retrieval Augmentation for Personalized Dialogue Generation
von: Huang, Qiushi, et al.
Veröffentlicht: (2024)

AskSport: Web Application for Sports Question-Answering
von: Onofre, Enzo B, et al.
Veröffentlicht: (2025)

Response Enhanced Semi-supervised Dialogue Query Generation
von: Huang, Jianheng, et al.
Veröffentlicht: (2023)

Shoot First, Ask Questions Later? Building Rational Agents that Explore and Act Like People
von: Grand, Gabriel, et al.
Veröffentlicht: (2025)

Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
von: Deng, Yihe, et al.
Veröffentlicht: (2023)

What Students Ask, How a Generative AI Assistant Responds: Exploring Higher Education Students' Dialogues on Learning Analytics Feedback
von: Uzun, Yildiz, et al.
Veröffentlicht: (2026)

Grounding Multimodal LLMs to Embodied Agents that Ask for Help with Reinforcement Learning
von: Ramrakhya, Ram, et al.
Veröffentlicht: (2025)

On Wednesdays, We Ask Questions: Optimizing "Active Listening" in Automated Legal Triage and Referral
von: Steenhuis, Quinten, et al.
Veröffentlicht: (2026)

Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code
von: Wu, Jie JW
Veröffentlicht: (2023)

HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement
von: Schouten, Marco, et al.
Veröffentlicht: (2026)

Asking the Right Questions: Improving Reasoning with Generated Stepping Stones
von: Hu, Hengyuan, et al.
Veröffentlicht: (2026)

This Treatment Works, Right? Evaluating LLM Sensitivity to Patient Question Framing in Medical QA
von: Yun, Hye Sun, et al.
Veröffentlicht: (2026)

QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
von: Kwak, Jaehyun, et al.
Veröffentlicht: (2025)

Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation
von: Abootorabi, Mohammad Mahdi, et al.
Veröffentlicht: (2025)

Enhanced Classroom Dialogue Sequences Analysis with a Hybrid AI Agent: Merging Expert Rule-Base with Large Language Models
von: Long, Yun, et al.
Veröffentlicht: (2024)

Ask2Loc: Learning to Locate Instructional Visual Answers by Asking Questions
von: Zong, Chang, et al.
Veröffentlicht: (2025)

May I Ask a Follow-up Question? Understanding the Benefits of Conversations in Neural Network Explainability
von: Zhang, Tong, et al.
Veröffentlicht: (2023)

Ask What Your Country Can Do For You: Towards a Public Red Teaming Model
von: Kennedy, Wm. Matthew, et al.
Veröffentlicht: (2025)