Cover Image

Knowing but Not Showing: LLMs Recognize Ambiguity but Rarely Ask Clarifying Questions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Su, Jinyan, Cardie, Claire
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Thinking Fast and Right: Balancing Accuracy and Reasoning Length with Adaptive Rewards
by: Su, Jinyan, et al.
Published: (2025)

Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs
by: Su, Jinyan, et al.
Published: (2025)

Adapting Fake News Detection to the Era of Large Language Models
by: Su, Jinyan, et al.
Published: (2023)

Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions
by: Zhang, Michael J. Q., et al.
Published: (2024)

CLIPer: Tailoring Diverse User Preference via Classifier-Guided Inference-Time Personalization
by: Su, Jinyan, et al.
Published: (2026)

Multi-Hop Question Answering: When Can Humans Help, and Where do They Struggle?
by: Su, Jinyan, et al.
Published: (2025)

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

Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questions
by: Dhole, Kaustubh D.
Published: (2020)

Teaching Vision-Language Models to Ask: Resolving Ambiguity in Visual Questions
by: Jian, Pu, et al.
Published: (2025)

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

I Could've Asked That: Reformulating Unanswerable Questions
by: Zhao, Wenting, et al.
Published: (2024)

Reasoning Court: Combining Reasoning, Action, and Judgment for Multi-Hop Reasoning
by: Wu, Jingtian, et al.
Published: (2025)

MASH: Modeling Abstention via Selective Help-Seeking
by: Gul, Mustafa Omer, et al.
Published: (2025)

ALFA: Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning
by: Li, Shuyue Stella, et al.
Published: (2025)

Learning to Ask Informative Questions: Enhancing LLMs with Preference Optimization and Expected Information Gain
by: Mazzaccara, Davide, et al.
Published: (2024)

Sparse Neurons Carry Strong Signals of Question Ambiguity in LLMs
by: Zhang, Zhuoxuan, et al.
Published: (2025)

Detecting Temporal Ambiguity in Questions
by: Piryani, Bhawna, et al.
Published: (2024)

HAPO: Training Language Models to Reason Concisely via History-Aware Policy Optimization
by: Huang, Chengyu, et al.
Published: (2025)

Ask, Answer, and Detect: Role-Playing LLMs for Personality Detection with Question-Conditioned Mixture-of-Experts
by: Lyu, Yifan, et al.
Published: (2025)

Do Images Clarify? A Study on the Effect of Images on Clarifying Questions in Conversational Search
by: Siro, Clemencia, et al.
Published: (2026)

AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs
by: Siro, Clemencia, et al.
Published: (2024)

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

Corpus Poisoning via Approximate Greedy Gradient Descent
by: Su, Jinyan, et al.
Published: (2024)

Knowing When to Ask -- Bridging Large Language Models and Data
by: Radhakrishnan, Prashanth, et al.
Published: (2024)

Token-weighted Direct Preference Optimization with Attention
by: Huang, Chengyu, et al.
Published: (2026)

To Know or Not To Know? Analyzing Self-Consistency of Large Language Models under Ambiguity
by: Sedova, Anastasiia, et al.
Published: (2024)

Estimating the Usefulness of Clarifying Questions and Answers for Conversational Search
by: Sekulić, Ivan, et al.
Published: (2024)

Mind the Ambiguity: Aleatoric Uncertainty Quantification in LLMs for Safe Medical Question Answering
by: Liu, Yaokun, et al.
Published: (2026)

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

AskQE: Question Answering as Automatic Evaluation for Machine Translation
by: Ki, Dayeon, et al.
Published: (2025)

LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations
by: Orgad, Hadas, et al.
Published: (2024)

A Gaze-grounded Visual Question Answering Dataset for Clarifying Ambiguous Japanese Questions
by: Inadumi, Shun, et al.
Published: (2024)

Asking Multimodal Clarifying Questions in Mixed-Initiative Conversational Search
by: Yuan, Yifei, et al.
Published: (2024)

TO-GATE: Clarifying Questions and Summarizing Responses with Trajectory Optimization for Eliciting Human Preference
by: Dou, Yulin, et al.
Published: (2025)

Clarification Is Not Enough: Post-Clarification Answering Remains the Bottleneck in Multi-Turn QA
by: Su, Jinyan, et al.
Published: (2026)

Bootstrapping Post-training Signals for Open-ended Tasks via Rubric-based Self-play on Pre-training Text
by: Huang, Chengyu, et al.
Published: (2026)

Knowing When to Ask: Segment-Level Credit Assignment for LLM Tool Use
by: Kumar, Abhijit, et al.
Published: (2026)

Do LLMs Understand Ambiguity in Text? A Case Study in Open-world Question Answering
by: Keluskar, Aryan, et al.
Published: (2024)

Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-reference
by: Shen, Kai, et al.
Published: (2024)

WildChat: 1M ChatGPT Interaction Logs in the Wild
by: Zhao, Wenting, et al.
Published: (2024)