A Tri-Agent Framework for Evaluating and Aligning Question Clarification Capabilities of Large Language Models

arXiv:2609.02054 · cs.CL · Submitted 2026-09-02 · Read on arXiv

cs.CL

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

• Benchmark — 14× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 12× in this paper · explained in 3 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Question Clarifying Agent — 6× in this paper
• Accuracy — 5× in this paper · explained in 1 episode
• Robustness — 5× in this paper · explained in 5 episodes
• Ambiguity Handling — 4× in this paper
• Dialogue Efficiency — 3× in this paper
• Evaluator Agent — 3× in this paper
• Overall Task Success — 3× in this paper
• Question Quality — 3× in this paper
• Respondent Agent — 3× in this paper
• Synthetic Data Generation — 3× in this paper · explained in 5 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Final Question Alignment — 2× in this paper
• Inter-Coder Reliability — 2× in this paper
• International Conference on Learning Representations — 2× in this paper
• Language Appropriateness — 2× in this paper
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Alignment with Perceived Ambiguity — 1× in this paper
• Hallucination — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• A Moving Surface Drag Model for LES of Wind over Waves
• G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
• Aligning Language Models to Explicitly Handle Ambiguity
• ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
• AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
• Is ChatGPT a Good NLG Evaluator? A Preliminary Study
• Can Large Language Models Really Improve by Self-critiquing Their Own Plans?
• BERTScore: Evaluating Text Generation with BERT
• CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information Needs in Large Language Models
• Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

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