Evaluating LLMs on Conversational Text-to-SQL under Chain Ambiguity and Intent Drift

arXiv:2608.29543 · cs.CL, cs.AI, cs.DB · Submitted 2026-08-30 · Read on arXiv

cs.CL, cs.AI, cs.DB

Submitted: 2026-08-30

Updated: 2026-08-30

Comments: Accepted to EMNLP2026 Main

Code: https://github.com/Rcrossmeister/TIDE-Bench

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Text-to-SQL — 37× in this paper · explained in 3 episodes
• Benchmark — 29× in this paper · explained in 2 episodes
• Accuracy — 19× in this paper · explained in 1 episode
• Aggregation — 10× in this paper · explained in 1 episode
• Core — 10× in this paper · explained in 2 episodes
• Failure Modes — 6× in this paper · explained in 3 episodes
• Trace — 6× in this paper · explained in 2 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• Knowledge Discovery and Data Mining — 3× in this paper
• Verification — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Commentary — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• In Association for Computational Linguistics — 2× in this paper
• In Empirical Methods in Natural Language Processing — 2× in this paper
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Very Large Data Bases — 2× in this paper
• Abstention — 1× in this paper · explained in 1 episode
• Agent Harness — 1× in this paper · explained in 1 episode
• Analyzer — 1× in this paper · explained in 1 episode
• Annotator Agreement — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Evaluation Dimensions — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• In International Conference on Learning Representations — 1× in this paper
• In-Context Learning — 1× in this paper · explained in 4 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems
• O1 Replication Journey: A Strategic Progress Report -- Part 1
• Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration
• HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help?
• Agentar-Scale-SQL: Advancing Text-to-SQL through Orchestrated Test-Time Scaling
• Benchmark Data Contamination of Large Language Models: A Survey
• Qwen2.5 Technical Report

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