{"total":38,"rows":[{"id":"2503.15850","title":"Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey","created":"2025-03-20","cited_by_count":95,"area":"lr"},{"id":"2304.05970","title":"Boosted Prompt Ensembles for Large Language Models","created":"2023-04-12","cited_by_count":36,"area":"lr"},{"id":"2505.16122","title":"Plan and Budget: Effective and Efficient Test-Time Scaling on Reasoning Large Language Models","created":"2025-05-22","cited_by_count":32,"area":"lr"},{"id":"2509.09675","title":"CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models","created":"2025-09-11","cited_by_count":29,"area":"lr"},{"id":"2502.17026","title":"Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topology","created":"2025-02-24","cited_by_count":25,"area":"lr"},{"id":"2505.11737","title":"TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning","created":"2025-05-16","cited_by_count":24,"area":"lr"},{"id":"2405.14039","title":"Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning","created":"2024-05-22","cited_by_count":18,"area":"lr"},{"id":"2410.10857","title":"Mirror-Consistency: Harnessing Inconsistency in Majority Voting","created":"2024-10-07","cited_by_count":17,"area":"lr"},{"id":"2505.20047","title":"Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks","created":"2025-05-26","cited_by_count":10,"area":"lr"},{"id":"2604.17112","title":"Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification","created":"2026-04-18","cited_by_count":10,"area":"lr"},{"id":"2605.04039","title":"Safety and accuracy follow different scaling laws in clinical large language models","created":"2026-05-05","cited_by_count":6,"area":"lr"},{"id":"2606.26080","title":"Neglected Free Lunch from Post-training: Progress Advantage for LLM Agents","created":"2026-06-24","cited_by_count":6,"area":"lr"},{"id":"2505.09591","title":"Variational Visual Question Answering for Uncertainty-Aware Selective Prediction","created":"2025-05-14","cited_by_count":5,"area":"lr"},{"id":"2601.09929","title":"Hallucination Detection and Mitigation in Large Language Models","created":"2026-01-14","cited_by_count":4,"area":"lr"},{"id":"2601.15296","title":"Entropy-Tree: Tree-Based Decoding with Entropy-Guided Exploration","created":"2026-01-02","cited_by_count":3,"area":"lr"},{"id":"2409.10044","title":"Benchmarking Large Language Model Uncertainty for Prompt Optimization","created":"2024-09-16","cited_by_count":2,"area":"lr"},{"id":"2512.09548","title":"Supporting Dynamic Agentic Workloads: How Data and Agents Interact","created":"2025-12-10","cited_by_count":2,"area":"lr"},{"id":"2602.17691","title":"Tethered Reasoning: Decoupling Entropy from Hallucination in Quantized LLMs via Manifold Steering","created":"2026-02-06","cited_by_count":2,"area":"lr"},{"id":"2605.18871","title":"Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning","created":"2026-05-15","cited_by_count":2,"area":"lr"},{"id":"2607.10139","title":"LLMs as a Jury: Cross-Model Consensus Can Outperform Process Reward Models for LLM Reasoning","created":"2026-07-11","cited_by_count":2,"area":"lr"},{"id":"2507.10007","title":"Deep Hidden Cognition Facilitates Reliable Chain-of-Thought Reasoning","created":"2025-07-14","cited_by_count":1,"area":"lr"},{"id":"2511.11916","title":"An Analysis of Architectural Impact on LLM-based Abstract Visual Reasoning: A Systematic Benchmark on RAVEN-FAIR","created":"2025-11-14","cited_by_count":1,"area":"lr"},{"id":"2511.17755","title":"CORA: Consistency-Guided Semi-Supervised Framework for Reasoning Segmentation","created":"2025-11-21","cited_by_count":1,"area":"lr"},{"id":"2602.08520","title":"Reinforcement Inference: Leveraging Uncertainty for Self-Correcting Language Model Reasoning","created":"2026-02-09","cited_by_count":1,"area":"lr"},{"id":"2606.30627","title":"Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models","created":"2026-06-29","cited_by_count":1,"area":"lr"},{"id":"2607.02182","title":"Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation","created":"2026-07-02","cited_by_count":1,"area":"lr"},{"id":"2509.13262","title":"Post-Hoc Split-Point Self-Consistency Verification for Efficient, Unified Quantification of Aleatoric and Epistemic Uncertainty in Deep Learning","created":"2025-09-16","cited_by_count":0,"area":"lr"},{"id":"2510.05176","title":"PatternKV: Flattening KV Representation Expands Quantization Headroom","created":"2025-10-05","cited_by_count":0,"area":"lr"},{"id":"2511.15921","title":"Thinking, Faithful and Stable: Mitigating Hallucinations in LLMs","created":"2025-11-19","cited_by_count":0,"area":"lr"},{"id":"2601.04271","title":"Correcting Autonomous Driving Object Detection Misclassifications with Automated Commonsense Reasoning","created":"2026-01-07","cited_by_count":0,"area":"lr"},{"id":"2602.15867","title":"Playing With AI: How Do State-Of-The-Art Large Language Models Perform in the 1977 Text-Based Adventure Game Zork?","created":"2026-01-27","cited_by_count":0,"area":"lr"},{"id":"2603.17811","title":"Dropout Robustness and Cognitive Profiling of Transformer Models via Stochastic Inference","created":"2026-03-18","cited_by_count":0,"area":"lr"},{"id":"2605.20033","title":"A Nash Equilibrium Framework For Training-Free Multimodal Step Verification","created":"2026-05-19","cited_by_count":0,"area":"lr"},{"id":"2605.30391","title":"Social Reasoning in Machines: Investigating Collective Truth-Seeking Dynamics in Large Language Model Debate","created":"2026-05-28","cited_by_count":0,"area":"lr"},{"id":"2606.18846","title":"From Bounding Boxes to Visual Reasoning: An On-Policy Data Annotation Tool for Vision-Language Models","created":"2026-06-17","cited_by_count":0,"area":"lr"},{"id":"2606.19812","title":"Human-on-the-Loop Orchestration for AI-Assisted Legal Discovery","created":"2026-06-18","cited_by_count":0,"area":"lr"},{"id":"2609.14438","title":"A latent dimension of Condorcet's jury theorem for multiple AI advisers","created":"2026-09-13","cited_by_count":0,"area":"lr"},{"id":"2610.00991","title":"Adapter Thickets: Splitting an RLVR Budget Beats Concentrating It","created":"2026-10-01","cited_by_count":0,"area":"lr"}],"next_cursor":null}