{"total":78,"rows":[{"id":"2312.10997","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","created":"2023-12-18","cited_by_count":2212,"area":"lr"},{"id":"2402.10963","title":"GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements","created":"2024-02-13","cited_by_count":103,"area":"lr"},{"id":"2501.18099","title":"Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge","created":"2025-01-30","cited_by_count":78,"area":"lr"},{"id":"2403.05313","title":"RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation","created":"2024-03-08","cited_by_count":75,"area":"lr"},{"id":"2502.01839","title":"Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification","created":"2025-02-03","cited_by_count":50,"area":"lr"},{"id":"2410.13080","title":"Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models","created":"2024-10-16","cited_by_count":48,"area":"lr"},{"id":"2410.10630","title":"Thinking LLMs: General Instruction Following with Thought Generation","created":"2024-10-14","cited_by_count":45,"area":"lr"},{"id":"2502.15815","title":"Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics","created":"2025-02-19","cited_by_count":34,"area":"lr"},{"id":"2406.03441","title":"Cycles of Thought: Measuring LLM Confidence through Stable Explanations","created":"2024-06-05","cited_by_count":29,"area":"lr"},{"id":"2404.12065","title":"RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models","created":"2024-04-18","cited_by_count":27,"area":"lr"},{"id":"2401.17686","title":"Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning","created":"2024-01-31","cited_by_count":24,"area":"lr"},{"id":"2505.09970","title":"Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents","created":"2025-05-15","cited_by_count":24,"area":"lr"},{"id":"2504.06438","title":"Don't Let It Hallucinate: Premise Verification via Retrieval-Augmented Logical Reasoning","created":"2025-04-08","cited_by_count":15,"area":"lr"},{"id":"2504.13828","title":"Generative AI Act II: Test Time Scaling Drives Cognition Engineering","created":"2025-04-18","cited_by_count":15,"area":"lr"},{"id":"2311.09603","title":"Self-Contradictory Reasoning Evaluation and Detection","created":"2023-11-16","cited_by_count":14,"area":"lr"},{"id":"2407.21443","title":"Improving Faithfulness of Large Language Models in Summarization via Sliding Generation and Self-Consistency","created":"2024-07-31","cited_by_count":14,"area":"lr"},{"id":"2505.17126","title":"Conformal Language Model Reasoning with Coherent Factuality","created":"2025-05-21","cited_by_count":14,"area":"lr"},{"id":"2510.16062","title":"Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs","created":"2025-10-17","cited_by_count":14,"area":"lr"},{"id":"2408.05093","title":"Order Matters in Hallucination: Reasoning Order as Benchmark and Reflexive Prompting for Large-Language-Models","created":"2024-08-09","cited_by_count":12,"area":"lr"},{"id":"2504.02181","title":"A Survey of Scaling in Large Language Model Reasoning","created":"2025-04-02","cited_by_count":10,"area":"lr"},{"id":"2504.14520","title":"Meta-Thinking in LLMs via Multi-Agent Reinforcement Learning: A Survey","created":"2025-04-20","cited_by_count":10,"area":"lr"},{"id":"2502.05675","title":"Investigating the Shortcomings of LLMs in Step-by-Step Legal Reasoning","created":"2025-02-08","cited_by_count":9,"area":"lr"},{"id":"2503.02003","title":"HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs","created":"2025-03-03","cited_by_count":9,"area":"lr"},{"id":"2402.17786","title":"Stepwise Self-Consistent Mathematical Reasoning with Large Language Models","created":"2024-02-24","cited_by_count":8,"area":"lr"},{"id":"2509.01544","title":"Causal Consistency Regularization: Training Verifiably Sensitive Reasoning in Large Language Models","created":"2025-09-01","cited_by_count":8,"area":"lr"},{"id":"2603.07379","title":"SoK: Agentic Retrieval-Augmented Generation (RAG): Taxonomy, Architectures, Evaluation, and Research Directions","created":"2026-03-07","cited_by_count":8,"area":"lr"},{"id":"2401.05787","title":"Chain of Evidences and Evidence to Generate: Prompting for Context Grounded and Retrieval Augmented Reasoning","created":"2024-01-11","cited_by_count":7,"area":"lr"},{"id":"2402.15631","title":"Fine-Grained Self-Endorsement Improves Factuality and Reasoning","created":"2024-02-23","cited_by_count":7,"area":"lr"},{"id":"2311.08390","title":"Predicting Text Preference Via Structured Comparative Reasoning","created":"2023-11-14","cited_by_count":6,"area":"lr"},{"id":"2410.01044","title":"RATIONALYST: Mining Implicit Rationales for Process Supervision of Reasoning","created":"2024-10-01","cited_by_count":6,"area":"lr"},{"id":"2508.12140","title":"Exploring Efficiency Frontiers of Thinking Budget in Medical Reasoning: Scaling Laws between Computational Resources and Reasoning Quality","created":"2025-08-16","cited_by_count":6,"area":"lr"},{"id":"2607.22962","title":"ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control","created":"2026-07-25","cited_by_count":6,"area":"lr"},{"id":"2607.28374","title":"LEDGERMIND: Provenance-Constrained Multimodal Agentic Reasoning with a Structured Evidence Ledger","created":"2026-07-30","cited_by_count":5,"area":"lr"},{"id":"2401.02132","title":"DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models","created":"2024-01-04","cited_by_count":4,"area":"lr"},{"id":"2402.11058","title":"II-MMR: Identifying and Improving Multi-modal Multi-hop Reasoning in Visual Question Answering","created":"2024-02-16","cited_by_count":4,"area":"lr"},{"id":"2409.06241","title":"DiPT: Enhancing LLM reasoning through diversified perspective-taking","created":"2024-09-10","cited_by_count":4,"area":"lr"},{"id":"2507.09751","title":"Sound and Complete Neurosymbolic Reasoning with LLM-Grounded Interpretations","created":"2025-07-13","cited_by_count":4,"area":"lr"},{"id":"2510.24320","title":"Critique-RL: Training Language Models for Critiquing through Two-Stage Reinforcement Learning","created":"2025-10-28","cited_by_count":4,"area":"lr"},{"id":"2404.09868","title":"Software Engineering Methods For AI-Driven Deductive Legal Reasoning","created":"2024-04-15","cited_by_count":3,"area":"lr"},{"id":"2501.11599","title":"SR-FoT: A Syllogistic-Reasoning Framework of Thought for Large Language Models Tackling Knowledge-based Reasoning Tasks","created":"2025-01-20","cited_by_count":3,"area":"lr"},{"id":"2508.17959","title":"Language Models Coupled with Metacognition Can Outperform Reasoning Models","created":"2025-08-25","cited_by_count":3,"area":"lr"},{"id":"2602.19281","title":"Limited Reasoning Space: The cage of long-horizon reasoning in LLMs","created":"2026-02-22","cited_by_count":3,"area":"lr"},{"id":"2606.22681","title":"Only Ask What You Don't Know: Grounded Delta Planning for Efficient Multi-step RAG","created":"2026-06-21","cited_by_count":3,"area":"lr"},{"id":"2406.13050","title":"Think-then-Act: A Dual-Angle Evaluated Retrieval-Augmented Generation","created":"2024-06-18","cited_by_count":2,"area":"lr"},{"id":"2506.10647","title":"Data Shifts Hurt CoT: A Theoretical Study","created":"2025-06-12","cited_by_count":2,"area":"lr"},{"id":"2506.23128","title":"Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons","created":"2025-06-29","cited_by_count":2,"area":"lr"},{"id":"2602.00085","title":"CARE-RFT: Confidence-Anchored Reinforcement Finetuning for Reliable Reasoning in Large Language Models","created":"2026-01-22","cited_by_count":2,"area":"lr"},{"id":"2604.04131","title":"Profile-Then-Reason: Bounded Semantic Complexity for Tool-Augmented Language Agents","created":"2026-04-05","cited_by_count":2,"area":"lr"},{"id":"2604.17912","title":"Learning to Correct: Calibrated Reinforcement Learning for Multi-Attempt Chain-of-Thought","created":"2026-04-20","cited_by_count":2,"area":"lr"},{"id":"2605.14163","title":"Agentic Systems as Boosting Weak Reasoning Models","created":"2026-05-13","cited_by_count":2,"area":"lr"},{"id":"2607.12650","title":"Evidence-Grounded Verified Agentic Reasoning: A Path Toward Eliminating LLM Hallucination in Empirical Inference via Tool-Attested Kernel Proofs","created":"2026-07-14","cited_by_count":2,"area":"lr"},{"id":"2503.03669","title":"Attentive Reasoning Queries: A Systematic Method for Optimizing Instruction-Following in Large Language Models","created":"2025-03-05","cited_by_count":1,"area":"lr"},{"id":"2507.00092","title":"Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models","created":"2025-06-30","cited_by_count":1,"area":"lr"},{"id":"2507.15015","title":"MetaCrit: A Critical Thinking Framework for Self-Regulated LLM Reasoning","created":"2025-07-20","cited_by_count":1,"area":"lr"},{"id":"2510.08992","title":"Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search","created":"2025-10-10","cited_by_count":1,"area":"lr"},{"id":"2510.18254","title":"Illusions of reflection: open-ended task reveals systematic failures in Large Language Models' reflective reasoning","created":"2025-10-21","cited_by_count":1,"area":"lr"},{"id":"2511.12861","title":"From Perception to Reasoning: Deep Thinking Empowers Multimodal Large Language Models","created":"2025-11-17","cited_by_count":1,"area":"lr"},{"id":"2512.20664","title":"Eidoku: A Neuro-Symbolic Verification Gate for LLM Reasoning via Structural Constraint Satisfaction","created":"2025-12-19","cited_by_count":1,"area":"lr"},{"id":"2601.01490","title":"Distortion Instead of Hallucination: The Effect of Reasoning Under Strict Constraints","created":"2026-01-04","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":"2606.21724","title":"Denoising Iterative Self-Correction: Structured Verification Loops for Reliable LLM Reasoning","created":"2026-06-19","cited_by_count":1,"area":"lr"},{"id":"2510.01674","title":"FOR-Prompting: From Objection to Revision via an Asymmetric Prompting Protocol","created":"2025-10-02","cited_by_count":0,"area":"lr"},{"id":"2510.10252","title":"Audit-of-Understanding: Posterior-Constrained Inference for Mathematical Reasoning in Language Models","created":"2025-10-11","cited_by_count":0,"area":"lr"},{"id":"2602.22508","title":"Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering","created":"2026-02-26","cited_by_count":0,"area":"lr"},{"id":"2604.04418","title":"Justified or Just Convincing? Error Verifiability as a Dimension of LLM Quality","created":"2026-04-06","cited_by_count":0,"area":"lr"},{"id":"2604.06269","title":"MAT-Cell: A Multi-Agent Tree-Structured Reasoning Framework for Batch-Level Single-Cell Annotation","created":"2026-04-07","cited_by_count":0,"area":"lr"},{"id":"2606.02054","title":"eMoT: evolving Memory-of-Thought via Symbolic Anchoring and Memory Corrosion","created":"2026-06-01","cited_by_count":0,"area":"lr"},{"id":"2606.02282","title":"POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems","created":"2026-06-01","cited_by_count":0,"area":"lr"},{"id":"2606.21867","title":"ForEx: A Formal Verification Framework for Explainable Reasoning in Logical Fallacy Detection and Annotation","created":"2026-06-20","cited_by_count":0,"area":"lr"},{"id":"2607.17417","title":"Grounded verification of chemical and materials reasoning: detection is the bottleneck","created":"2026-07-19","cited_by_count":0,"area":"lr"},{"id":"2607.17823","title":"Theoretical Foundations of $\\max$@$k$ Reinforcement Learning","created":"2026-07-20","cited_by_count":0,"area":"lr"},{"id":"2608.11420","title":"Social Chain of Thought: A Multi-Agent Architecture Grounded in Medical Differential Diagnosis Methodology","created":"2026-08-11","cited_by_count":0,"area":"lr"},{"id":"2608.30426","title":"Learning to Reason and Use Tools through Unsupervised Fine-Tuning in Task-Oriented Dialog Systems","created":"2026-08-31","cited_by_count":0,"area":"lr"},{"id":"2609.26610","title":"Semantic Abstraction for Natural Language Inference: a Methodological Framework for Discovering and Compensating Semantic Knowledge and Reasoning Gaps in Large Language Models","created":"2026-09-22","cited_by_count":0,"area":"lr"},{"id":"2609.33297","title":"The Error You See Is Not the Error You Made: Progression-aware Reasoning Origin for Reasoning Error Localization","created":"2026-09-27","cited_by_count":0,"area":"lr"},{"id":"2609.39478","title":"Also Small Models Can Reasonably Self-Evaluate Their Confidence","created":"2026-09-30","cited_by_count":0,"area":"lr"},{"id":"2610.00940","title":"ReHoPER: Receding-Horizon Planning for Enhanced Reasoning","created":"2026-10-01","cited_by_count":0,"area":"lr"},{"id":"2610.07018","title":"When to Rethink: Learning Multi-Perspective Self-Verification for Vision-Language Models","created":"2026-10-04","cited_by_count":0,"area":"lr"}],"next_cursor":null}