{"total":50,"rows":[{"id":"2410.01679","title":"VinePPO: Refining Credit Assignment in RL Training of LLMs","created":"2024-10-02","cited_by_count":183,"area":null},{"id":"2410.20290","title":"Fast Best-of-N Decoding via Speculative Rejection","created":"2024-10-26","cited_by_count":112,"area":null},{"id":"2409.07431","title":"Synthetic continued pretraining","created":"2024-09-11","cited_by_count":60,"area":null},{"id":"2602.20133","title":"AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization","created":"2026-02-23","cited_by_count":60,"area":null},{"id":"2607.07663","title":"Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops","created":"2026-07-08","cited_by_count":35,"area":null},{"id":"2503.10084","title":"Why Prompt Design Matters and Works: A Complexity Analysis of Prompt Search Space in LLMs","created":"2025-03-13","cited_by_count":31,"area":null},{"id":"2502.11027","title":"On the Effect of Sampling Diversity in Scaling LLM Inference","created":"2025-02-16","cited_by_count":18,"area":null},{"id":"2411.11504","title":"Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering","created":"2024-11-18","cited_by_count":16,"area":null},{"id":"2601.12471","title":"Knowing When to Abstain: Medical LLMs Under Clinical Uncertainty","created":"2026-01-18","cited_by_count":15,"area":null},{"id":"2503.14481","title":"Don't lie to your friends: Learning what you know from collaborative self-play","created":"2025-03-18","cited_by_count":14,"area":null},{"id":"2409.17972","title":"BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search","created":"2024-09-26","cited_by_count":13,"area":null},{"id":"2511.13211","title":"3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale","created":"2025-11-17","cited_by_count":12,"area":null},{"id":"2505.23179","title":"DIP-R1: Deep Inspection and Perception with RL Looking Through and Understanding Complex Scenes","created":"2025-05-29","cited_by_count":11,"area":null},{"id":"2502.01609","title":"Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search","created":"2025-02-03","cited_by_count":10,"area":null},{"id":"2506.07443","title":"LegalReasoner: Step-wised Verification-Correction for Legal Judgment Reasoning","created":"2025-06-09","cited_by_count":9,"area":null},{"id":"2508.05995","title":"Optimizing Prompt Sequences using Monte Carlo Tree Search for LLM-Based Optimization","created":"2025-08-08","cited_by_count":9,"area":null},{"id":"2510.03199","title":"Best-of-Majority: Minimax-Optimal Strategy for Pass@$k$ Inference Scaling","created":"2025-10-03","cited_by_count":9,"area":null},{"id":"2602.12966","title":"ProbeLLM: Automating Principled Diagnosis of LLM Failures","created":"2026-02-13","cited_by_count":9,"area":null},{"id":"2407.08642","title":"Towards Building Specialized Generalist AI with System 1 and System 2 Fusion","created":"2024-07-11","cited_by_count":8,"area":null},{"id":"2602.20532","title":"Actor-Curator: Co-adaptive Curriculum Learning via Policy-Improvement Bandits for RL Post-Training","created":"2026-02-24","cited_by_count":8,"area":null},{"id":"2604.07941","title":"Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning","created":"2026-04-09","cited_by_count":6,"area":null},{"id":"2503.21383","title":"Controlling Large Language Model with Latent Actions","created":"2025-03-27","cited_by_count":5,"area":null},{"id":"2504.07527","title":"Supervised Optimism Correction: Be Confident When LLMs Are Sure","created":"2025-04-10","cited_by_count":5,"area":null},{"id":"2508.01724","title":"ReflecSched: Solving Dynamic Flexible Job-Shop Scheduling via LLM-Powered Hierarchical Reflection","created":"2025-08-03","cited_by_count":5,"area":null},{"id":"2509.21791","title":"Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference","created":"2025-09-26","cited_by_count":5,"area":null},{"id":"2512.04068","title":"Learning Steerable Clarification Policies with Collaborative Self-play","created":"2025-12-03","cited_by_count":5,"area":null},{"id":"2509.01328","title":"Can Large Language Models Master Complex Card Games?","created":"2025-09-01","cited_by_count":4,"area":null},{"id":"2406.17809","title":"Towards a Science Exocortex","created":"2024-06-24","cited_by_count":3,"area":null},{"id":"2507.18858","title":"Weak-to-Strong Generalization with Failure Trajectories: A Tree-based Approach to Elicit Optimal Policy in Strong Models","created":"2025-07-25","cited_by_count":3,"area":null},{"id":"2508.11184","title":"Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction","created":"2025-08-15","cited_by_count":3,"area":null},{"id":"2512.00672","title":"ML-Tool-Bench: Tool-Augmented Planning for ML Tasks","created":"2025-11-29","cited_by_count":3,"area":null},{"id":"2503.04750","title":"AI Agents Should be Regulated Based on the Extent of Their Autonomous Operations","created":"2025-02-07","cited_by_count":2,"area":null},{"id":"2506.07557","title":"SELT: Self-Evaluation Tree Search for LLMs with Task Decomposition","created":"2025-06-09","cited_by_count":2,"area":null},{"id":"2512.01827","title":"CauSight: Learning to Supersense for Visual Causal Discovery","created":"2025-12-01","cited_by_count":2,"area":null},{"id":"2511.21706","title":"A General Highly Accurate Online Planning Method Integrating Large Language Models into Nested Rollout Policy Adaptation for Dialogue Tasks","created":"2025-11-17","cited_by_count":1,"area":null},{"id":"2608.07494","title":"How to Ask the AI: A User Perspective Survey for Large Language Model Prompting","created":"2026-06-17","cited_by_count":1,"area":null},{"id":"2608.14375","title":"Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages","created":"2026-08-14","cited_by_count":1,"area":null},{"id":"2608.18027","title":"Chain-of-Experience for Continual LLM Improvement","created":"2026-08-18","cited_by_count":1,"area":null},{"id":"2608.26582","title":"J-Zero: Unified Challenger--Solver--Judge Self-Evolution from Zero Data","created":"2026-08-27","cited_by_count":1,"area":null},{"id":"2609.39102","title":"False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents","created":"2026-09-30","cited_by_count":1,"area":null},{"id":"2505.17288","title":"Learning to Choose or Choosing to Learn: Best-of-N vs. Supervised Fine-Tuning for Bit String Generation","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2512.05336","title":"PathFinder: MCTS and LLM Feedback-based Path Selection for Multi-Hop Question Answering","created":"2025-12-05","cited_by_count":0,"area":null},{"id":"2601.08653","title":"Prism: Towards Lowering User Cognitive Load in LLMs via Complex Intent Understanding","created":"2026-01-13","cited_by_count":0,"area":null},{"id":"2604.08454","title":"Less Data Approximates More: Earning Faithful Confidence in High-Stakes Domains","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2605.28109","title":"Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization","created":"2026-05-27","cited_by_count":0,"area":null},{"id":"2606.00618","title":"Efficient Test-time Inference for Generative Planning Models with OCL Search","created":"2026-05-30","cited_by_count":0,"area":null},{"id":"2607.02390","title":"DecompRL: Solving Harder Problems by Learning Modular Code Generation","created":"2026-07-02","cited_by_count":0,"area":null},{"id":"2608.06216","title":"Continual Learning in Transition","created":"2026-08-06","cited_by_count":0,"area":null},{"id":"2610.02023","title":"SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RL","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.17666","title":"DeltaTTG: Training Multi-Turn Agents with a Token-to-Go Progress Meter","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}