{"total":128,"rows":[{"id":"2204.01691","title":"Do As I Can, Not As I Say: Grounding Language in Robotic Affordances","created":"2022-04-04","cited_by_count":2348,"area":null},{"id":"2307.05973","title":"VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models","created":"2023-07-12","cited_by_count":750,"area":null},{"id":"2209.11302","title":"ProgPrompt: Generating Situated Robot Task Plans using Large Language Models","created":"2022-09-22","cited_by_count":611,"area":null},{"id":"2210.03094","title":"VIMA: General Robot Manipulation with Multimodal Prompts","created":"2022-10-06","cited_by_count":407,"area":null},{"id":"2302.07241","title":"ConceptFusion: Open-set Multimodal 3D Mapping","created":"2023-02-14","cited_by_count":304,"area":null},{"id":"2209.00626","title":"The Alignment Problem from a Deep Learning Perspective","created":"2022-08-30","cited_by_count":258,"area":null},{"id":"2305.03514","title":"Can Large Language Models Transform Computational Social Science?","created":"2023-04-12","cited_by_count":250,"area":null},{"id":"2307.04721","title":"Large Language Models as General Pattern Machines","created":"2023-07-10","cited_by_count":197,"area":null},{"id":"2302.02662","title":"Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning","created":"2023-02-06","cited_by_count":195,"area":null},{"id":"2212.10789","title":"Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing","created":"2022-12-21","cited_by_count":166,"area":null},{"id":"2303.04129","title":"Foundation Models for Decision Making: Problems, Methods, and Opportunities","created":"2023-03-07","cited_by_count":164,"area":null},{"id":"2310.10625","title":"Video Language Planning","created":"2023-10-16","cited_by_count":162,"area":null},{"id":"2305.11854","title":"Multimodal Web Navigation with Instruction-Finetuned Foundation Models","created":"2023-05-19","cited_by_count":160,"area":null},{"id":"2206.06565","title":"LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks","created":"2022-06-14","cited_by_count":148,"area":null},{"id":"2302.05128","title":"Translating Natural Language to Planning Goals with Large-Language Models","created":"2023-02-10","cited_by_count":133,"area":null},{"id":"2209.03430","title":"Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions","created":"2022-09-07","cited_by_count":116,"area":null},{"id":"2305.11176","title":"Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model","created":"2023-05-18","cited_by_count":116,"area":null},{"id":"2404.00282","title":"Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods","created":"2024-03-30","cited_by_count":116,"area":null},{"id":"2308.13111","title":"Bayesian Low-rank Adaptation for Large Language Models","created":"2023-08-24","cited_by_count":115,"area":null},{"id":"2403.00811","title":"Cognitive Bias in Decision-Making with LLMs","created":"2024-02-25","cited_by_count":106,"area":null},{"id":"2312.08782","title":"Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis","created":"2023-12-14","cited_by_count":103,"area":null},{"id":"2401.08743","title":"MMToM-QA: Multimodal Theory of Mind Question Answering","created":"2024-01-16","cited_by_count":85,"area":null},{"id":"2307.01848","title":"Embodied Task Planning with Large Language Models","created":"2023-07-04","cited_by_count":84,"area":null},{"id":"2502.11221","title":"PlanGenLLMs: A Modern Survey of LLM Planning Capabilities","created":"2025-02-16","cited_by_count":83,"area":null},{"id":"2308.13724","title":"ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning","created":"2023-08-26","cited_by_count":77,"area":null},{"id":"2308.01399","title":"Learning to Model the World with Language","created":"2023-07-31","cited_by_count":68,"area":null},{"id":"2310.00035","title":"LoRA ensembles for large language model fine-tuning","created":"2023-09-29","cited_by_count":67,"area":null},{"id":"2206.10680","title":"Learning Neuro-Symbolic Skills for Bilevel Planning","created":"2022-06-21","cited_by_count":58,"area":null},{"id":"2204.05080","title":"Semantic Exploration from Language Abstractions and Pretrained Representations","created":"2022-04-08","cited_by_count":51,"area":null},{"id":"2301.03044","title":"A Survey on Transformers in Reinforcement Learning","created":"2023-01-08","cited_by_count":50,"area":null},{"id":"2406.04428","title":"MoralBench: Moral Evaluation of LLMs","created":"2024-06-06","cited_by_count":50,"area":null},{"id":"2305.14330","title":"DirecT2V: Large Language Models are Frame-Level Directors for Zero-Shot Text-to-Video Generation","created":"2023-05-23","cited_by_count":49,"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":"2406.13163","title":"LLMatDesign: Autonomous Materials Discovery with Large Language Models","created":"2024-06-19","cited_by_count":42,"area":null},{"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":"2205.12258","title":"History Compression via Language Models in Reinforcement Learning","created":"2022-05-24","cited_by_count":39,"area":null},{"id":"2212.14164","title":"On Transforming Reinforcement Learning by Transformer: The Development Trajectory","created":"2022-12-29","cited_by_count":36,"area":null},{"id":"2303.16563","title":"Skill Reinforcement Learning and Planning for Open-World Long-Horizon Tasks","created":"2023-03-29","cited_by_count":36,"area":null},{"id":"2401.14151","title":"True Knowledge Comes from Practice: Aligning LLMs with Embodied Environments via Reinforcement Learning","created":"2024-01-25","cited_by_count":36,"area":null},{"id":"2310.19619","title":"Towards A Holistic Landscape of Situated Theory of Mind in Large Language Models","created":"2023-10-30","cited_by_count":32,"area":null},{"id":"2401.12975","title":"HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments","created":"2024-01-23","cited_by_count":32,"area":null},{"id":"2210.03821","title":"Large Language Models can Implement Policy Iteration","created":"2022-10-07","cited_by_count":31,"area":null},{"id":"2308.05737","title":"Follow Anything: Open-set detection, tracking, and following in real-time","created":"2023-08-10","cited_by_count":29,"area":null},{"id":"2311.17944","title":"PALM: Predicting Actions through Language Models","created":"2023-11-29","cited_by_count":29,"area":null},{"id":"2210.11522","title":"Composing Ensembles of Pre-trained Models via Iterative Consensus","created":"2022-10-20","cited_by_count":28,"area":null},{"id":"2304.09179","title":"Pretrained Language Models as Visual Planners for Human Assistance","created":"2023-04-17","cited_by_count":28,"area":null},{"id":"2305.11598","title":"Introspective Tips: Large Language Model for In-Context Decision Making","created":"2023-05-19","cited_by_count":28,"area":null},{"id":"2407.13237","title":"LLM-Empowered State Representation for Reinforcement Learning","created":"2024-07-18","cited_by_count":28,"area":null},{"id":"2312.06876","title":"Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks","created":"2023-12-11","cited_by_count":27,"area":null},{"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":"2406.18851","title":"LICO: Large Language Models for In-Context Molecular Optimization","created":"2024-06-27","cited_by_count":26,"area":null},{"id":"2505.00026","title":"Theory of Mind in Large Language Models: Assessment and Enhancement","created":"2025-04-26","cited_by_count":25,"area":null},{"id":"2306.11886","title":"SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling","created":"2023-06-20","cited_by_count":24,"area":null},{"id":"2402.14807","title":"A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health","created":"2024-02-22","cited_by_count":24,"area":null},{"id":"2405.13245","title":"A Survey of Robotic Language Grounding: Tradeoffs between Symbols and Embeddings","created":"2024-05-21","cited_by_count":24,"area":null},{"id":"2406.17675","title":"Evaluating Large Language Models with Psychometrics","created":"2024-06-25","cited_by_count":22,"area":null},{"id":"2210.04964","title":"Generating Executable Action Plans with Environmentally-Aware Language Models","created":"2022-10-10","cited_by_count":21,"area":null},{"id":"2301.09017","title":"Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?","created":"2023-01-21","cited_by_count":21,"area":null},{"id":"2309.10092","title":"Conformal Temporal Logic Planning using Large Language Models","created":"2023-09-18","cited_by_count":21,"area":null},{"id":"2310.08922","title":"LLaMA Rider: Spurring Large Language Models to Explore the Open World","created":"2023-10-13","cited_by_count":21,"area":null},{"id":"2409.16022","title":"AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment","created":"2024-09-24","cited_by_count":20,"area":null},{"id":"2211.03959","title":"Pretraining in Deep Reinforcement Learning: A Survey","created":"2022-11-08","cited_by_count":18,"area":null},{"id":"2402.15368","title":"Probabilistically Correct Language-based Multi-Robot Planning using Conformal Prediction","created":"2024-02-23","cited_by_count":18,"area":null},{"id":"2306.09312","title":"Semantic HELM: A Human-Readable Memory for Reinforcement Learning","created":"2023-06-15","cited_by_count":17,"area":null},{"id":"2405.19883","title":"From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems","created":"2024-05-30","cited_by_count":17,"area":null},{"id":"2406.04344","title":"Verbalized Machine Learning: Revisiting Machine Learning with Language Models","created":"2024-06-06","cited_by_count":17,"area":null},{"id":"2402.00251","title":"Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning","created":"2024-02-01","cited_by_count":16,"area":null},{"id":"2310.09676","title":"Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning","created":"2023-10-14","cited_by_count":15,"area":null},{"id":"2404.09043","title":"Do LLMs Play Dice? Exploring Probability Distribution Sampling in Large Language Models for Behavioral Simulation","created":"2024-04-13","cited_by_count":14,"area":null},{"id":"2402.16181","title":"How Can LLM Guide RL? A Value-Based Approach","created":"2024-02-25","cited_by_count":13,"area":null},{"id":"2502.15336","title":"Exploring Embodied Multimodal Large Models: Development, Datasets, and Future Directions","created":"2025-02-21","cited_by_count":13,"area":null},{"id":"2308.09830","title":"Synergistic Integration of Large Language Models and Cognitive Architectures for Robust AI: An Exploratory Analysis","created":"2023-08-18","cited_by_count":11,"area":null},{"id":"2210.01287","title":"Robot Task Planning and Situation Handling in Open Worlds","created":"2022-10-04","cited_by_count":10,"area":null},{"id":"2501.07468","title":"From Screens to Scenes: A Survey of Embodied AI in Healthcare","created":"2025-01-13","cited_by_count":10,"area":null},{"id":"2311.02171","title":"Emergence of Abstract State Representations in Embodied Sequence Modeling","created":"2023-11-03","cited_by_count":9,"area":null},{"id":"2312.01097","title":"Planning as In-Painting: A Diffusion-Based Embodied Task Planning Framework for Environments under Uncertainty","created":"2023-12-02","cited_by_count":9,"area":null},{"id":"2404.02649","title":"On the Importance of Uncertainty in Decision-Making with Large Language Models","created":"2024-04-03","cited_by_count":9,"area":null},{"id":"2409.01806","title":"LASP: Surveying the State-of-the-Art in Large Language Model-Assisted AI Planning","created":"2024-09-03","cited_by_count":9,"area":null},{"id":"2504.04578","title":"Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification","created":"2025-04-06","cited_by_count":9,"area":null},{"id":"2303.04912","title":"Embodied Active Learning of Relational State Abstractions for Bilevel Planning","created":"2023-03-08","cited_by_count":8,"area":null},{"id":"2303.16189","title":"Planning with Sequence Models through Iterative Energy Minimization","created":"2023-03-28","cited_by_count":8,"area":null},{"id":"2507.03194","title":"Quantifying Cognitive Bias Induction in LLM-Generated Content","created":"2025-07-03","cited_by_count":7,"area":null},{"id":"2604.07774","title":"RoboAgent: Chaining Basic Capabilities for Embodied Task Planning","created":"2026-04-09","cited_by_count":7,"area":null},{"id":"2303.09031","title":"A Picture is Worth a Thousand Words: Language Models Plan from Pixels","created":"2023-03-16","cited_by_count":6,"area":null},{"id":"2312.06408","title":"DiffVL: Scaling Up Soft Body Manipulation using Vision-Language Driven Differentiable Physics","created":"2023-12-11","cited_by_count":6,"area":null},{"id":"2410.06431","title":"Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs","created":"2024-10-09","cited_by_count":6,"area":null},{"id":"2308.13542","title":"LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying","created":"2023-08-21","cited_by_count":5,"area":null},{"id":"2403.08109","title":"VANP: Learning Where to See for Navigation with Self-Supervised Vision-Action Pre-Training","created":"2024-03-12","cited_by_count":5,"area":null},{"id":"2504.01472","title":"ANNEXE: Unified Analyzing, Answering, and Pixel Grounding for Egocentric Interaction","created":"2025-04-02","cited_by_count":5,"area":null},{"id":"2604.18463","title":"Using large language models for embodied planning introduces systematic safety risks","created":"2026-04-20","cited_by_count":5,"area":null},{"id":"2308.13782","title":"Planning with Logical Graph-based Language Model for Instruction Generation","created":"2023-08-26","cited_by_count":4,"area":null},{"id":"2309.13059","title":"Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education","created":"2023-09-09","cited_by_count":4,"area":null},{"id":"2312.03881","title":"FoMo Rewards: Can we cast foundation models as reward functions?","created":"2023-12-06","cited_by_count":4,"area":null},{"id":"2401.03388","title":"LLMs for Robotic Object Disambiguation","created":"2024-01-07","cited_by_count":4,"area":null},{"id":"2407.03964","title":"Improving Sample Efficiency of Reinforcement Learning with Background Knowledge from Large Language Models","created":"2024-07-04","cited_by_count":4,"area":null},{"id":"2410.01440","title":"Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling","created":"2024-10-02","cited_by_count":4,"area":null},{"id":"2503.19007","title":"Option Discovery Using LLM-guided Semantic Hierarchical Reinforcement Learning","created":"2025-03-24","cited_by_count":4,"area":null},{"id":"2505.09901","title":"Comparing Exploration-Exploitation Strategies of LLMs and Humans: Insights from Standard Multi-armed Bandit Experiments","created":"2025-05-15","cited_by_count":4,"area":null},{"id":"2202.07138","title":"Integrating AI Planning with Natural Language Processing: A Combination of Explicit and Tacit Knowledge","created":"2022-02-15","cited_by_count":3,"area":null},{"id":"2205.13079","title":"Learning to Query Internet Text for Informing Reinforcement Learning Agents","created":"2022-05-25","cited_by_count":3,"area":null}],"next_cursor":"100"}