{"list":"other","total":53,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396},{"id":"1405.0312","title":"Microsoft COCO: Common Objects in Context","created":"2014-05-01","cited_by_count":17608},{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"2407.21783","title":"The Llama 3 Herd of Models","created":"2024-07-31","cited_by_count":14715},{"id":"1908.10084","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","created":"2019-08-27","cited_by_count":9170},{"id":"1904.09675","title":"BERTScore: Evaluating Text Generation with BERT","created":"2019-04-21","cited_by_count":5512},{"id":"1409.4842","title":"Going Deeper with Convolutions","created":"2014-09-17","cited_by_count":4241},{"id":"2307.15818","title":"RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control","created":"2023-07-28","cited_by_count":3080},{"id":"2406.09246","title":"OpenVLA: An Open-Source Vision-Language-Action Model","created":"2024-06-13","cited_by_count":2887},{"id":"2410.24164","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","created":"2024-10-31","cited_by_count":2407},{"id":"2304.13705","title":"Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware","created":"2023-04-23","cited_by_count":1568},{"id":"1803.10122","title":"World Models","created":"2018-03-27","cited_by_count":1513},{"id":"2306.03310","title":"LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning","created":"2023-06-05","cited_by_count":1410},{"id":"2503.14734","title":"GR00T N1: An Open Foundation Model for Generalist Humanoid Robots","created":"2025-03-18","cited_by_count":1225},{"id":"1708.00055","title":"SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation","created":"2017-07-31","cited_by_count":1001},{"id":"2601.03267","title":"OpenAI GPT-5 System Card","created":"2025-12-19","cited_by_count":989},{"id":"2501.03575","title":"Cosmos World Foundation Model Platform for Physical AI","created":"2025-01-07","cited_by_count":864},{"id":"1909.12271","title":"RLBench: The Robot Learning Benchmark & Learning Environment","created":"2019-09-26","cited_by_count":689},{"id":"2112.03227","title":"CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks","created":"2021-12-06","cited_by_count":584},{"id":"2501.15830","title":"SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model","created":"2025-01-27","cited_by_count":519},{"id":"2405.05941","title":"Evaluating Real-World Robot Manipulation Policies in Simulation","created":"2024-05-09","cited_by_count":495},{"id":"2406.02523","title":"RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots","created":"2024-06-04","cited_by_count":407},{"id":"1703.09312","title":"Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics","created":"2017-03-27","cited_by_count":264},{"id":"2412.18194","title":"VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks","created":"2024-12-24","cited_by_count":175},{"id":"2411.14499","title":"Understanding World or Predicting Future? A Comprehensive Survey of World Models","created":"2024-11-21","cited_by_count":166},{"id":"2507.16815","title":"ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning","created":"2025-07-22","cited_by_count":156},{"id":"2507.21504","title":"Evaluation and Benchmarking of LLM Agents: A Survey","created":"2025-07-29","cited_by_count":152},{"id":"2308.02828","title":"An Empirical Study of the Non-determinism of ChatGPT in Code Generation","created":"2023-08-05","cited_by_count":137},{"id":"1309.2660","title":"Data-Driven Grasp Synthesis - A Survey","created":"2013-09-10","cited_by_count":106},{"id":"2510.03342","title":"Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer","created":"2025-10-02","cited_by_count":87},{"id":"2109.09262","title":"TOGA: A Neural Method for Test Oracle Generation","created":"2021-09-20","cited_by_count":57},{"id":"2305.00418","title":"Using Large Language Models to Generate JUnit Tests: An Empirical Study","created":"2023-04-30","cited_by_count":53},{"id":"2409.12894","title":"VLATest: Testing and Evaluating Vision-Language-Action Models for Robotic Manipulation","created":"2024-09-19","cited_by_count":45},{"id":"2403.15852","title":"SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents","created":"2024-03-23","cited_by_count":34},{"id":"2505.15660","title":"Exploring the Limits of Vision-Language-Action Manipulations in Cross-task Generalization","created":"2025-05-21","cited_by_count":33},{"id":"2405.03786","title":"TOGLL: Correct and Strong Test Oracle Generation with LLMs","created":"2024-05-06","cited_by_count":24},{"id":"2506.09930","title":"From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Models","created":"2025-06-11","cited_by_count":23},{"id":"2508.15503","title":"Guidelines for Empirical Studies in Software Engineering involving Large Language Models","created":"2025-08-21","cited_by_count":21},{"id":"2511.02097","title":"A Step Toward World Models: A Survey on Robotic Manipulation","created":"2025-10-31","cited_by_count":15},{"id":"2410.05191","title":"LADEV: A Language-Driven Testing and Evaluation Platform for Vision-Language-Action Models in Robotic Manipulation","created":"2024-10-07","cited_by_count":9},{"id":"2506.02943","title":"Hallucination to Consensus: Multi-Agent LLMs for End-to-End JUnit Test Generation","created":"2025-06-03","cited_by_count":9},{"id":"2407.16974","title":"SelfPiCo: Self-Guided Partial Code Execution with LLMs","created":"2024-07-24","cited_by_count":7},{"id":"2505.02931","title":"The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models","created":"2025-05-05","cited_by_count":7},{"id":"2602.22579","title":"Metamorphic Testing of Vision-Language Action-Enabled Robots","created":"2026-02-26","cited_by_count":5},{"id":"2501.17461","title":"AugmenTest: Enhancing Tests with LLM-Driven Oracles","created":"2025-01-29","cited_by_count":4},{"id":"2502.16071","title":"Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models","created":"2025-02-22","cited_by_count":4},{"id":"2505.20324","title":"Evaluating the Energy-Efficiency of the Code Generated by LLMs","created":"2025-05-23","cited_by_count":4},{"id":"2510.26423","title":"Nexus: Execution-Grounded Multi-Agent Test Oracle Synthesis","created":"2025-10-30","cited_by_count":4},{"id":"2405.15450","title":"Faster and Better Quantum Software Testing through Specification Reduction and Projective Measurements","created":"2024-05-24","cited_by_count":3},{"id":"1903.03399","title":"Generating Automated and Online Test Oracles for Simulink Models with Continuous and Uncertain Behaviors","created":"2019-03-08","cited_by_count":1},{"id":"2605.10408","title":"VISOR: A Vision-Language Model-based Test Oracle for Testing Robots","created":"2026-05-11","cited_by_count":1},{"id":"2606.10465","title":"MASTOR: A Multi-Agent Approach to Semantic Test Oracle Generation for RESTful APIs","created":"2026-06-09","cited_by_count":1}],"next_cursor":null}