{"total":308,"rows":[{"id":"2203.07814","title":"Competition-Level Code Generation with AlphaCode","created":"2022-02-08","cited_by_count":1462,"area":"lr"},{"id":"2203.14465","title":"STaR: Bootstrapping Reasoning With Reasoning","created":"2022-03-28","cited_by_count":940,"area":"lr"},{"id":"2408.15240","title":"Generative Verifiers: Reward Modeling as Next-Token Prediction","created":"2024-08-27","cited_by_count":480,"area":"lr"},{"id":"2502.05171","title":"Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach","created":"2025-02-07","cited_by_count":415,"area":"lr"},{"id":"2209.14610","title":"Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning","created":"2022-09-29","cited_by_count":350,"area":"lr"},{"id":"2502.17419","title":"From System 1 to System 2: A Survey of Reasoning Large Language Models","created":"2025-02-24","cited_by_count":320,"area":"lr"},{"id":"2210.03849","title":"ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering","created":"2022-10-07","cited_by_count":196,"area":"lr"},{"id":"2303.12501","title":"Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval","created":"2023-03-22","cited_by_count":132,"area":"lr"},{"id":"2304.03843","title":"Why think step by step? Reasoning emerges from the locality of experience","created":"2023-04-07","cited_by_count":103,"area":"lr"},{"id":"2505.16400","title":"AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning","created":"2025-05-22","cited_by_count":87,"area":"lr"},{"id":"2503.16252","title":"Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning","created":"2025-03-20","cited_by_count":83,"area":"lr"},{"id":"2412.15084","title":"AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling","created":"2024-12-19","cited_by_count":77,"area":"lr"},{"id":"2411.16646","title":"Self-Generated Critiques Boost Reward Modeling for Language Models","created":"2024-11-25","cited_by_count":71,"area":"lr"},{"id":"2502.08606","title":"Distillation Scaling Laws","created":"2025-02-12","cited_by_count":67,"area":"lr"},{"id":"2404.02657","title":"Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models","created":"2024-04-03","cited_by_count":65,"area":"lr"},{"id":"2501.04686","title":"Unlocking Multimodal Mathematical Reasoning via Process Reward Model","created":"2025-01-08","cited_by_count":65,"area":"lr"},{"id":"2506.17211","title":"BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning","created":"2025-06-20","cited_by_count":63,"area":"lr"},{"id":"2205.10128","title":"Neural-Symbolic Models for Logical Queries on Knowledge Graphs","created":"2022-05-16","cited_by_count":61,"area":"lr"},{"id":"2311.06753","title":"AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs","created":"2023-11-12","cited_by_count":59,"area":"lr"},{"id":"2403.04483","title":"GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability","created":"2024-03-07","cited_by_count":58,"area":"lr"},{"id":"2305.11490","title":"LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation","created":"2023-05-19","cited_by_count":57,"area":"lr"},{"id":"2305.19555","title":"Large Language Models Are Not Strong Abstract Reasoners","created":"2023-05-31","cited_by_count":53,"area":"lr"},{"id":"2408.08640","title":"Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning","created":"2024-08-16","cited_by_count":52,"area":"lr"},{"id":"2507.04632","title":"Can Prompt Difficulty be Online Predicted for Accelerating RL Finetuning of Reasoning Models?","created":"2025-07-07","cited_by_count":52,"area":"lr"},{"id":"2306.05415","title":"Causal normalizing flows: from theory to practice","created":"2023-06-08","cited_by_count":51,"area":"lr"},{"id":"2512.13607","title":"Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models","created":"2025-12-15","cited_by_count":48,"area":"lr"},{"id":"2503.18878","title":"I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders","created":"2025-03-24","cited_by_count":45,"area":"lr"},{"id":"2510.04871","title":"Less is More: Recursive Reasoning with Tiny Networks","created":"2025-10-06","cited_by_count":45,"area":"lr"},{"id":"2203.10316","title":"Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction","created":"2022-03-19","cited_by_count":44,"area":"lr"},{"id":"2403.06447","title":"CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation","created":"2024-03-11","cited_by_count":44,"area":"lr"},{"id":"2202.04800","title":"The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning","created":"2022-02-10","cited_by_count":38,"area":"lr"},{"id":"2202.05826","title":"End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking","created":"2022-02-11","cited_by_count":33,"area":"lr"},{"id":"2312.07399","title":"Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales","created":"2023-12-12","cited_by_count":33,"area":"lr"},{"id":"2509.19128","title":"PipelineRL: Faster On-policy Reinforcement Learning for Long Sequence Generation","created":"2025-09-23","cited_by_count":32,"area":"lr"},{"id":"2202.04178","title":"VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming","created":"2022-02-07","cited_by_count":31,"area":"lr"},{"id":"2307.02768","title":"Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts","created":"2023-07-06","cited_by_count":31,"area":"lr"},{"id":"2408.14511","title":"Unveiling the Statistical Foundations of Chain-of-Thought Prompting Methods","created":"2024-08-25","cited_by_count":29,"area":"lr"},{"id":"2410.05459","title":"From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency","created":"2024-10-07","cited_by_count":29,"area":"lr"},{"id":"2211.17113","title":"Weisfeiler and Leman Go Relational","created":"2022-11-30","cited_by_count":28,"area":"lr"},{"id":"2310.14747","title":"MCC-KD: Multi-CoT Consistent Knowledge Distillation","created":"2023-10-23","cited_by_count":28,"area":"lr"},{"id":"2401.07286","title":"CANDLE: Iterative Conceptualization and Instantiation Distillation from Large Language Models for Commonsense Reasoning","created":"2024-01-14","cited_by_count":28,"area":"lr"},{"id":"2503.08540","title":"Mellow: a small audio language model for reasoning","created":"2025-03-11","cited_by_count":27,"area":"lr"},{"id":"2505.18086","title":"Stable Reinforcement Learning for Efficient Reasoning","created":"2025-05-23","cited_by_count":27,"area":"lr"},{"id":"2304.11107","title":"ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT","created":"2023-04-21","cited_by_count":26,"area":"lr"},{"id":"2510.00977","title":"It Takes Two: Your GRPO Is Secretly DPO","created":"2025-10-01","cited_by_count":26,"area":"lr"},{"id":"2305.04808","title":"CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoning","created":"2023-05-08","cited_by_count":25,"area":"lr"},{"id":"2507.09075","title":"OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique","created":"2025-07-11","cited_by_count":25,"area":"lr"},{"id":"2306.06891","title":"Recursion of Thought: A Divide-and-Conquer Approach to Multi-Context Reasoning with Language Models","created":"2023-06-12","cited_by_count":24,"area":"lr"},{"id":"2310.10180","title":"TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models","created":"2023-10-16","cited_by_count":24,"area":"lr"},{"id":"2507.05418","title":"Learn Globally, Speak Locally: Bridging the Gaps in Multilingual Reasoning","created":"2025-07-07","cited_by_count":24,"area":"lr"},{"id":"2205.13720","title":"Effective Abstract Reasoning with Dual-Contrast Network","created":"2022-05-27","cited_by_count":23,"area":"lr"},{"id":"2312.15194","title":"PokeMQA: Programmable knowledge editing for Multi-hop Question Answering","created":"2023-12-23","cited_by_count":23,"area":"lr"},{"id":"2409.15156","title":"Rethinking Conventional Wisdom in Machine Learning: From Generalization to Scaling","created":"2024-09-23","cited_by_count":23,"area":"lr"},{"id":"2502.03860","title":"BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation","created":"2025-02-06","cited_by_count":23,"area":"lr"},{"id":"2509.16645","title":"ADVEDM:Fine-grained Adversarial Attack against VLM-based Embodied Agents","created":"2025-09-20","cited_by_count":23,"area":"lr"},{"id":"2509.21655","title":"DriftLite: Lightweight Drift Control for Inference-Time Scaling of Diffusion Models","created":"2025-09-25","cited_by_count":23,"area":"lr"},{"id":"2306.02797","title":"Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language","created":"2023-06-05","cited_by_count":22,"area":"lr"},{"id":"2402.10688","title":"Towards Uncovering How Large Language Model Works: An Explainability Perspective","created":"2024-02-16","cited_by_count":22,"area":"lr"},{"id":"2403.14349","title":"On the Concept Trustworthiness in Concept Bottleneck Models","created":"2024-03-21","cited_by_count":22,"area":"lr"},{"id":"2210.12040","title":"Neuro-Symbolic Causal Reasoning Meets Signaling Game for Emergent Semantic Communications","created":"2022-10-21","cited_by_count":21,"area":"lr"},{"id":"2210.15578","title":"GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphs","created":"2022-10-27","cited_by_count":21,"area":"lr"},{"id":"2511.05993","title":"Revisiting Entropy in Reinforcement Learning for Large Reasoning Models","created":"2025-11-08","cited_by_count":21,"area":"lr"},{"id":"2207.12576","title":"WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models","created":"2022-07-25","cited_by_count":20,"area":"lr"},{"id":"2306.02500","title":"Systematic Visual Reasoning through Object-Centric Relational Abstraction","created":"2023-06-04","cited_by_count":20,"area":"lr"},{"id":"2309.03224","title":"No Train Still Gain. Unleash Mathematical Reasoning of Large Language Models with Monte Carlo Tree Search Guided by Energy Function","created":"2023-09-01","cited_by_count":20,"area":"lr"},{"id":"2503.16024","title":"The Lighthouse of Language: Enhancing LLM Agents via Critique-Guided Improvement","created":"2025-03-20","cited_by_count":20,"area":"lr"},{"id":"2503.17604","title":"OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery","created":"2025-03-22","cited_by_count":20,"area":"lr"},{"id":"2505.24511","title":"Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting","created":"2025-05-30","cited_by_count":20,"area":"lr"},{"id":"2509.25502","title":"Seeing Before Reasoning: A Unified Framework for Generalizable and Explainable Fake Image Detection","created":"2025-09-29","cited_by_count":20,"area":"lr"},{"id":"2303.02260","title":"Learning to reason over visual objects","created":"2023-03-03","cited_by_count":19,"area":"lr"},{"id":"2305.18898","title":"AlphaBlock: Embodied Finetuning for Vision-Language Reasoning in Robot Manipulation","created":"2023-05-30","cited_by_count":19,"area":"lr"},{"id":"2404.16807","title":"Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning","created":"2024-04-25","cited_by_count":19,"area":"lr"},{"id":"2406.01145","title":"Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering","created":"2024-06-03","cited_by_count":19,"area":"lr"},{"id":"2410.17635","title":"Markov Chain of Thought for Efficient Mathematical Reasoning","created":"2024-10-23","cited_by_count":19,"area":"lr"},{"id":"2212.08286","title":"ALERT: Adapting Language Models to Reasoning Tasks","created":"2022-12-16","cited_by_count":17,"area":"lr"},{"id":"2408.03533","title":"Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation","created":"2024-08-07","cited_by_count":17,"area":"lr"},{"id":"2507.14958","title":"MUR: Momentum Uncertainty guided Reasoning for Large Language Models","created":"2025-07-20","cited_by_count":17,"area":"lr"},{"id":"2204.02380","title":"CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations","created":"2022-04-05","cited_by_count":16,"area":"lr"},{"id":"2305.07716","title":"Learning to Reason over Scene Graphs: A Case Study of Finetuning GPT-2 into a Robot Language Model for Grounded Task Planning","created":"2023-05-12","cited_by_count":16,"area":"lr"},{"id":"2309.08859","title":"Rethinking Learning Rate Tuning in the Era of Large Language Models","created":"2023-09-16","cited_by_count":16,"area":"lr"},{"id":"2510.15414","title":"MARSHAL: Incentivizing Multi-Agent Reasoning via Self-Play with Strategic LLMs","created":"2025-10-17","cited_by_count":16,"area":"lr"},{"id":"2204.10448","title":"Hypergraph Transformer: Weakly-supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering","created":"2022-04-22","cited_by_count":15,"area":"lr"},{"id":"2207.14000","title":"Multi-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation","created":"2022-07-28","cited_by_count":15,"area":"lr"},{"id":"2512.17436","title":"Xiaomi MiMo-VL-Miloco Technical Report","created":"2025-12-19","cited_by_count":15,"area":"lr"},{"id":"2210.10105","title":"ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler","created":"2022-10-18","cited_by_count":14,"area":"lr"},{"id":"2210.12887","title":"Retrieval Augmentation for Commonsense Reasoning: A Unified Approach","created":"2022-10-23","cited_by_count":14,"area":"lr"},{"id":"2505.22524","title":"Inference-Time Scaling of Discrete Diffusion Models via Importance Weighting and Optimal Proposal Design","created":"2025-05-28","cited_by_count":14,"area":"lr"},{"id":"2602.01970","title":"Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models","created":"2026-02-02","cited_by_count":14,"area":"lr"},{"id":"2602.05547","title":"Multi-Task GRPO: Reliable LLM Reasoning Across Tasks","created":"2026-02-05","cited_by_count":14,"area":"lr"},{"id":"2205.14307","title":"TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph","created":"2022-05-28","cited_by_count":13,"area":"lr"},{"id":"2310.06214","title":"CoT3DRef: Chain-of-Thoughts Data-Efficient 3D Visual Grounding","created":"2023-10-10","cited_by_count":13,"area":"lr"},{"id":"2402.03507","title":"Neural networks for abstraction and reasoning: Towards broad generalization in machines","created":"2024-02-05","cited_by_count":13,"area":"lr"},{"id":"2412.08519","title":"Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation","created":"2024-12-11","cited_by_count":13,"area":"lr"},{"id":"2509.26628","title":"Attention as a Compass: Efficient Exploration for Process-Supervised RL in Reasoning Models","created":"2025-09-30","cited_by_count":13,"area":"lr"},{"id":"2206.04928","title":"GAMR: A Guided Attention Model for (visual) Reasoning","created":"2022-06-10","cited_by_count":12,"area":"lr"},{"id":"2206.11212","title":"VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives","created":"2022-06-22","cited_by_count":12,"area":"lr"},{"id":"2303.15714","title":"Explicit Planning Helps Language Models in Logical Reasoning","created":"2023-03-28","cited_by_count":12,"area":"lr"},{"id":"2307.00928","title":"Learning Differentiable Logic Programs for Abstract Visual Reasoning","created":"2023-07-03","cited_by_count":12,"area":"lr"},{"id":"2406.03068","title":"Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers","created":"2024-06-05","cited_by_count":12,"area":"lr"},{"id":"2602.00449","title":"Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks","created":"2026-01-31","cited_by_count":12,"area":"lr"}],"next_cursor":"100"}