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Action Generation

Papers

Showing 125 of 111 papers

TitleStatusHype
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient RoboticsCode11
Large Action Models: From Inception to ImplementationCode9
Fine-Tuning Vision-Language-Action Models: Optimizing Speed and SuccessCode5
WorldVLA: Towards Autoregressive Action World ModelCode4
AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-TuningCode3
Distilling LLM Agent into Small Models with Retrieval and Code ToolsCode3
Flow Q-LearningCode3
Affordance-based Robot Manipulation with Flow MatchingCode3
AutoScraper: A Progressive Understanding Web Agent for Web Scraper GenerationCode3
PokeLLMon: A Human-Parity Agent for Pokemon Battles with Large Language ModelsCode3
Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and TrendsCode2
InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative ReasonersCode2
Prior Does Matter: Visual Navigation via Denoising Diffusion Bridge ModelsCode2
Agent models: Internalizing Chain-of-Action Generation into Reasoning modelsCode2
LiteWebAgent: The Open-Source Suite for VLM-Based Web-Agent ApplicationsCode2
What Makes a Good Diffusion Planner for Decision Making?Code2
Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous DrivingCode2
Learning Physically Realizable Skills for Online Packing of General 3D ShapesCode2
Time to Talk: LLM Agents for Asynchronous Group Communication in Mafia GamesCode1
OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data SynthesisCode1
LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile AppsCode1
Mini Diffuser: Fast Multi-task Diffusion Policy Training Using Two-level Mini-batchesCode1
Large Language Models for Multi-Robot Systems: A SurveyCode1
Benchmarking Vision, Language, & Action Models on Robotic Learning TasksCode1
EPO: Hierarchical LLM Agents with Environment Preference OptimizationCode1
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