Video2Skill: From Streaming Experience to Reusable Embodied Skills

arXiv:2609.36691 · cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Project page: https://andyzworks.github.io/video2skill

Terminology

• Benchmark — 12× in this paper · explained in 2 episodes
• Abstraction — 8× in this paper · explained in 1 episode
• Streaming Embodied Skill Discovery — 5× in this paper
• Continual Learning — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Reinforcement Learning — 4× in this paper · explained in 4 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Inverse Problem — 2× in this paper · explained in 2 episodes
• Vision-language models — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adjusted Rand Index — 1× in this paper
• Affordance — 1× in this paper · explained in 1 episode
• Agent Harness — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Annotation Errors — 1× in this paper · explained in 1 episode
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• On-Policy Distillation — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Temporal Abstraction — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• Qwen2.5-VL Technical Report
• SCAR: Self-Supervised Continuous Action Representation Learning
• Code as Agent Harness
• SkillWrapper: Generative Predicate Invention for Task-level Robot Planning
• MEMORA: Embodied Action Memory from Egocentric Videos for Reasoning and Planning
• Progress Reward Modeling for Robotic Learning: A Comprehensive Survey
• SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering