{"total":19,"rows":[{"id":"2505.06120","title":"LLMs Get Lost In Multi-Turn Conversation","created":"2025-05-09","cited_by_count":429,"area":null},{"id":"2510.06552","title":"Flipping the Dialogue: Training and Evaluating User Language Models","created":"2025-10-08","cited_by_count":58,"area":null},{"id":"2411.07237","title":"Contextualized Evaluations: Judging Language Model Responses to Underspecified Queries","created":"2024-11-11","cited_by_count":12,"area":null},{"id":"2605.09808","title":"Quantifying the Utility of User Simulators for Building Collaborative LLM Assistants","created":"2026-05-10","cited_by_count":10,"area":null},{"id":"2607.20734","title":"LLMs Get Lost in Evolving User Intent","created":"2026-07-22","cited_by_count":10,"area":null},{"id":"2602.07338","title":"Intent Mismatch Causes LLMs to Get Lost in Multi-Turn Conversation","created":"2026-02-07","cited_by_count":9,"area":null},{"id":"2604.15597","title":"LLMs Corrupt Your Documents When You Delegate","created":"2026-04-17","cited_by_count":9,"area":null},{"id":"2510.18731","title":"Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards","created":"2025-10-21","cited_by_count":6,"area":null},{"id":"2509.23166","title":"Test-Time Policy Adaptation for Enhanced Multi-Turn Interactions with LLMs","created":"2025-09-27","cited_by_count":3,"area":null},{"id":"2601.15330","title":"ICPO: Illocution-Calibrated Policy Optimization for Multi-Turn Conversation","created":"2026-01-20","cited_by_count":2,"area":null},{"id":"2605.24432","title":"Found in Conversation: LLMs Teach Themselves to Close the Multi-Turn Gap","created":"2026-05-23","cited_by_count":2,"area":null},{"id":"2412.17411","title":"Pretraining with random noise for uncertainty calibration","created":"2024-12-23","cited_by_count":1,"area":null},{"id":"2602.11938","title":"Who is the richest club in the championship? Detecting and Rewriting Underspecified Questions Improve QA Performance","created":"2026-02-12","cited_by_count":1,"area":null},{"id":"2605.26788","title":"SeDT: Sentence-Transformer Decision-Transformer Conditioning for Multi-Turn Conversation Reliability","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2607.10428","title":"Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging","created":"2026-07-11","cited_by_count":1,"area":null},{"id":"2605.25204","title":"Clarification Is Not Enough: Post-Clarification Answering Remains the Bottleneck in Multi-Turn QA","created":"2026-05-24","cited_by_count":0,"area":null},{"id":"2605.28170","title":"Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values","created":"2026-05-27","cited_by_count":0,"area":null},{"id":"2606.20588","title":"AInterviewer: A Platform for Designing and Conducting AI-led Qualitative Interviews","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2608.00018","title":"CITBench: A Comprehensive Benchmark for Interactive Tabular Data Processing with LLMs","created":"2026-06-29","cited_by_count":0,"area":null}],"next_cursor":null}