{"total":231,"rows":[{"id":"2402.02716","title":"Understanding the planning of LLM agents: A survey","created":"2024-02-05","cited_by_count":421,"area":"agents"},{"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":"2405.14093","title":"A Survey on Vision-Language-Action Models for Embodied AI","created":"2024-05-23","cited_by_count":279,"area":"vla"},{"id":"2401.02051","title":"Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model","created":"2024-01-04","cited_by_count":268,"area":null},{"id":"2406.07155","title":"Scaling Large Language Model-based Multi-Agent Collaboration","created":"2024-06-11","cited_by_count":241,"area":"agents"},{"id":"2407.06886","title":"Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI","created":"2024-07-09","cited_by_count":179,"area":null},{"id":"2411.14499","title":"Understanding World or Predicting Future? A Comprehensive Survey of World Models","created":"2024-11-21","cited_by_count":166,"area":"wm"},{"id":"2312.03664","title":"Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia","created":"2023-12-06","cited_by_count":126,"area":"agents"},{"id":"2402.12275","title":"WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment","created":"2024-02-19","cited_by_count":107,"area":"wm"},{"id":"2408.09559","title":"HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Model","created":"2024-08-18","cited_by_count":106,"area":"lr"},{"id":"2408.15978","title":"WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Exploration","created":"2024-08-28","cited_by_count":101,"area":"agents"},{"id":"2406.05761","title":"The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models","created":"2024-06-09","cited_by_count":93,"area":null},{"id":"2401.04334","title":"Large Language Models for Robotics: Opportunities, Challenges, and Perspectives","created":"2024-01-09","cited_by_count":89,"area":"mllm"},{"id":"2408.00764","title":"AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation","created":"2024-08-01","cited_by_count":83,"area":"lr"},{"id":"2501.07278","title":"Lifelong Learning of Large Language Model based Agents: A Roadmap","created":"2025-01-13","cited_by_count":83,"area":"agents"},{"id":"2502.11221","title":"PlanGenLLMs: A Modern Survey of LLM Planning Capabilities","created":"2025-02-16","cited_by_count":83,"area":null},{"id":"2501.11425","title":"Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training","created":"2025-01-20","cited_by_count":82,"area":"lr"},{"id":"2603.11137","title":"Scaling Reasoning Efficiently via Relaxed On-Policy Distillation","created":"2026-03-11","cited_by_count":82,"area":"lr"},{"id":"2406.05804","title":"A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning","created":"2024-06-09","cited_by_count":74,"area":"agents"},{"id":"2410.08001","title":"Towards Synergistic, Generalized, and Efficient Dual-System for Robotic Manipulation","created":"2024-10-10","cited_by_count":73,"area":"vla"},{"id":"2505.20732","title":"SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution","created":"2025-05-27","cited_by_count":73,"area":"agents"},{"id":"2311.11797","title":"Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents","created":"2023-11-20","cited_by_count":72,"area":"lr"},{"id":"2405.14205","title":"Agent Planning with World Knowledge Model","created":"2024-05-23","cited_by_count":70,"area":"wm"},{"id":"2509.22642","title":"WoW: Towards a World omniscient World model Through Embodied Interaction","created":"2025-09-26","cited_by_count":67,"area":"wm"},{"id":"2410.16033","title":"TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling","created":"2024-10-18","cited_by_count":61,"area":"lr"},{"id":"2309.15028","title":"Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding","created":"2023-09-26","cited_by_count":60,"area":"lr"},{"id":"2503.11951","title":"SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning","created":"2025-03-15","cited_by_count":60,"area":"agents"},{"id":"2503.22458","title":"Evaluating LLM-based Agents for Multi-Turn Conversations: A Survey","created":"2025-03-28","cited_by_count":57,"area":"agents"},{"id":"2506.19676","title":"A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures","created":"2025-06-24","cited_by_count":57,"area":"agents"},{"id":"2311.15249","title":"Algorithm Evolution Using Large Language Model","created":"2023-11-26","cited_by_count":53,"area":null},{"id":"2402.01207","title":"Efficient Causal Graph Discovery Using Large Language Models","created":"2024-02-02","cited_by_count":53,"area":null},{"id":"2406.20095","title":"LLaRA: Supercharging Robot Learning Data for Vision-Language Policy","created":"2024-06-28","cited_by_count":52,"area":"mllm"},{"id":"2509.18970","title":"LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions","created":"2025-09-23","cited_by_count":50,"area":"agents"},{"id":"2310.08582","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","created":"2023-10-12","cited_by_count":48,"area":"lr"},{"id":"2411.01679","title":"Autoformulation of Mathematical Optimization Models Using LLMs","created":"2024-11-03","cited_by_count":48,"area":null},{"id":"2310.07889","title":"LangNav: Language as a Perceptual Representation for Navigation","created":"2023-10-11","cited_by_count":47,"area":null},{"id":"2404.11891","title":"Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools","created":"2024-04-18","cited_by_count":47,"area":null},{"id":"2405.14314","title":"Towards Efficient LLM Grounding for Embodied Multi-Agent Collaboration","created":"2024-05-23","cited_by_count":45,"area":"lr"},{"id":"2407.13943","title":"Werewolf Arena: A Case Study in LLM Evaluation via Social Deduction","created":"2024-07-18","cited_by_count":45,"area":null},{"id":"2409.15146","title":"COHERENT: Collaboration of Heterogeneous Multi-Robot System with Large Language Models","created":"2024-09-23","cited_by_count":45,"area":"lr"},{"id":"2310.07263","title":"CoPAL: Corrective Planning of Robot Actions with Large Language Models","created":"2023-10-11","cited_by_count":40,"area":null},{"id":"2401.02500","title":"On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)","created":"2024-01-04","cited_by_count":40,"area":null},{"id":"2404.19664","title":"Towards Generalist Robot Learning from Internet Video: A Survey","created":"2024-04-30","cited_by_count":40,"area":null},{"id":"2505.19683","title":"Large Language Models for Planning: A Comprehensive and Systematic Survey","created":"2025-05-26","cited_by_count":40,"area":"lr"},{"id":"2402.03271","title":"Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models","created":"2024-02-05","cited_by_count":39,"area":"lr"},{"id":"2404.03647","title":"Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra","created":"2024-04-04","cited_by_count":37,"area":null},{"id":"2410.02189","title":"Agent-Oriented Planning in Multi-Agent Systems","created":"2024-10-03","cited_by_count":36,"area":"agents"},{"id":"2407.16711","title":"Benchmarks as Microscopes: A Call for Model Metrology","created":"2024-07-22","cited_by_count":35,"area":null},{"id":"2312.12009","title":"Active Preference Inference using Language Models and Probabilistic Reasoning","created":"2023-12-19","cited_by_count":29,"area":"lr"},{"id":"2305.17590","title":"Integrating Action Knowledge and LLMs for Task Planning and Situation Handling in Open Worlds","created":"2023-05-27","cited_by_count":26,"area":null},{"id":"2407.15073","title":"Multi-Agent Causal Discovery Using Large Language Models","created":"2024-07-21","cited_by_count":26,"area":"agents"},{"id":"2410.07484","title":"WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents","created":"2024-10-09","cited_by_count":26,"area":"wm"},{"id":"2503.10480","title":"World Modeling Makes a Better Planner: Dual Preference Optimization for Embodied Task Planning","created":"2025-03-13","cited_by_count":26,"area":"wm"},{"id":"2510.04040","title":"FaithCoT-Bench: Benchmarking Instance-Level Faithfulness of Chain-of-Thought Reasoning","created":"2025-10-05","cited_by_count":26,"area":"lr"},{"id":"2402.04210","title":"Task Success is not Enough: Investigating the Use of Video-Language Models as Behavior Critics for Catching Undesirable Agent Behaviors","created":"2024-02-06","cited_by_count":25,"area":"agents"},{"id":"2503.04919","title":"FirePlace: Geometric Refinements of LLM Common Sense Reasoning for 3D Object Placement","created":"2025-03-06","cited_by_count":25,"area":"lr"},{"id":"2503.10814","title":"Thinking Machines: A Survey of LLM based Reasoning Strategies","created":"2025-03-13","cited_by_count":25,"area":"lr"},{"id":"2402.06025","title":"Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning","created":"2024-02-08","cited_by_count":24,"area":"lr"},{"id":"2410.10479","title":"TMGBench: A Systematic Game Benchmark for Evaluating Strategic Reasoning Abilities of LLMs","created":"2024-10-14","cited_by_count":24,"area":"lr"},{"id":"2602.19128","title":"K-Search: LLM Kernel Generation via Co-Evolving Intrinsic World Model","created":"2026-02-22","cited_by_count":24,"area":"wm"},{"id":"2502.11520","title":"AURORA:Automated Training Framework of Universal Process Reward Models via Ensemble Prompting and Reverse Verification","created":"2025-02-17","cited_by_count":23,"area":"lr"},{"id":"2405.16376","title":"STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making","created":"2024-05-25","cited_by_count":22,"area":"lr"},{"id":"2504.16855","title":"Monte Carlo Planning with Large Language Model for Text-Based Game Agents","created":"2025-04-23","cited_by_count":22,"area":"agents"},{"id":"2410.19034","title":"Mixture of Parrots: Experts improve memorization more than reasoning","created":"2024-10-24","cited_by_count":21,"area":"moe"},{"id":"2501.10069","title":"A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks","created":"2025-01-17","cited_by_count":21,"area":"lr"},{"id":"2502.20508","title":"TripCraft: A Benchmark for Spatio-Temporally Fine Grained Travel Planning","created":"2025-02-27","cited_by_count":21,"area":null},{"id":"2404.02817","title":"A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches","created":"2024-04-03","cited_by_count":20,"area":null},{"id":"2402.10778","title":"AutoGPT+P: Affordance-based Task Planning with Large Language Models","created":"2024-02-16","cited_by_count":19,"area":"lr"},{"id":"2502.12130","title":"Scaling Autonomous Agents via Automatic Reward Modeling And Planning","created":"2025-02-17","cited_by_count":19,"area":"lr"},{"id":"2405.19586","title":"SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation","created":"2024-05-30","cited_by_count":18,"area":null},{"id":"2506.09049","title":"VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning","created":"2025-06-10","cited_by_count":18,"area":"mllm"},{"id":"2502.12435","title":"A Survey on Large Language Models for Automated Planning","created":"2025-02-18","cited_by_count":17,"area":null},{"id":"2408.03247","title":"Unveiling Factual Recall Behaviors of Large Language Models through Knowledge Neurons","created":"2024-08-06","cited_by_count":16,"area":null},{"id":"2503.04094","title":"Pok\\'eChamp: an Expert-level Minimax Language Agent","created":"2025-03-06","cited_by_count":16,"area":"agents"},{"id":"2505.11122","title":"Navigating the Alpha Jungle: An LLM-Powered MCTS Framework for Formulaic Factor Mining","created":"2025-05-16","cited_by_count":16,"area":null},{"id":"2511.19515","title":"Fewer Tokens, Greater Scaling: Self-Adaptive Visual Bases for Efficient and Expansive Representation Learning","created":"2025-11-24","cited_by_count":16,"area":null},{"id":"2311.17406","title":"LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model","created":"2023-11-29","cited_by_count":15,"area":null},{"id":"2407.05138","title":"Are LLMs Correctly Integrated into Software Systems?","created":"2024-07-06","cited_by_count":15,"area":"rag"},{"id":"2503.00870","title":"NeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks In Open Domains","created":"2025-03-02","cited_by_count":15,"area":null},{"id":"2406.01238","title":"EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs","created":"2024-06-03","cited_by_count":14,"area":null},{"id":"2406.17659","title":"DKPROMPT: Domain Knowledge Prompting Vision-Language Models for Open-World Planning","created":"2024-06-25","cited_by_count":14,"area":"mllm"},{"id":"2502.10090","title":"Manual2Skill: Learning to Read Manuals and Acquire Robotic Skills for Furniture Assembly Using Vision-Language Models","created":"2025-02-14","cited_by_count":14,"area":null},{"id":"2503.20124","title":"Synthesizing world models for bilevel planning","created":"2025-03-26","cited_by_count":14,"area":"wm"},{"id":"2507.12846","title":"Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering","created":"2025-07-17","cited_by_count":14,"area":null},{"id":"2309.10103","title":"Reasoning about the Unseen for Efficient Outdoor Object Navigation","created":"2023-09-18","cited_by_count":13,"area":"lr"},{"id":"2410.14682","title":"ET-Plan-Bench: Embodied Task-level Planning Benchmark Towards Spatial-Temporal Cognition with Foundation Models","created":"2024-10-02","cited_by_count":13,"area":null},{"id":"2505.07027","title":"LLM-Augmented Chemical Synthesis and Design Decision Programs","created":"2025-05-11","cited_by_count":13,"area":null},{"id":"2402.11534","title":"PreAct: Prediction Enhances Agent's Planning Ability","created":"2024-02-18","cited_by_count":12,"area":"agents"},{"id":"2409.17140","title":"AXIS: Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents","created":"2024-09-25","cited_by_count":12,"area":"agents"},{"id":"2502.02390","title":"CoAT: Chain-of-Associated-Thoughts Framework for Enhancing Large Language Models Reasoning","created":"2025-02-04","cited_by_count":12,"area":"lr"},{"id":"2511.00962","title":"A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis","created":"2025-11-02","cited_by_count":12,"area":null},{"id":"2511.02424","title":"ReAcTree: Hierarchical LLM Agent Trees with Control Flow for Long-Horizon Task Planning","created":"2025-11-04","cited_by_count":12,"area":"agents"},{"id":"2308.14328","title":"Reinforcement Learning for Generative AI: A Survey","created":"2023-08-28","cited_by_count":11,"area":null},{"id":"2408.13184","title":"Can LLM be a Good Path Planner based on Prompt Engineering? Mitigating the Hallucination for Path Planning","created":"2024-08-23","cited_by_count":11,"area":"lr"},{"id":"2502.19805","title":"Implicit Search via Discrete Diffusion: A Study on Chess","created":"2025-02-27","cited_by_count":11,"area":"diffusion"},{"id":"2506.03880","title":"RadialRouter: Structured Representation for Efficient and Robust Large Language Models Routing","created":"2025-06-04","cited_by_count":11,"area":null},{"id":"2305.17760","title":"Language Models are Bounded Pragmatic Speakers: Understanding RLHF from a Bayesian Cognitive Modeling Perspective","created":"2023-05-28","cited_by_count":10,"area":"alignment"},{"id":"2504.08148","title":"Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI","created":"2025-04-10","cited_by_count":9,"area":"agents"},{"id":"2506.21230","title":"World-aware Planning Narratives Enhance Large Vision-Language Model Planner","created":"2025-06-26","cited_by_count":9,"area":"lr"},{"id":"2506.23127","title":"Unleashing Embodied Task Planning Ability in LLMs via Reinforcement Learning","created":"2025-06-29","cited_by_count":9,"area":null}],"next_cursor":"100"}