EchoPath: Execution-Level Replayable Memory for GUI Agents

arXiv:2609.16635 · cs.AI · Submitted 2026-09-15 · Read on arXiv

cs.AI

Submitted: 2026-09-15

Updated: 2026-09-15

Code: https://github.com/JackZhao1998/EchoPath

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Grounding — 39× in this paper · explained in 3 episodes
• Verification — 11× in this paper · explained in 2 episodes
• Trace — 9× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Core — 6× in this paper · explained in 2 episodes
• Image-based Target-Reaiming — 5× in this paper
• Model-Agnostic — 5× in this paper · explained in 2 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Agentic Framework — 4× in this paper · explained in 6 episodes
• Benchmarking — 4× in this paper · explained in 3 episodes
• Provenance — 4× in this paper · explained in 4 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Model Context Protocol — 3× in this paper
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Action Space — 2× in this paper · explained in 1 episode
• Model Context Protocol (MCP) — 2× in this paper · explained in 8 episodes
• Verifier — 2× in this paper · explained in 2 episodes
• Actio — 1× in this paper · explained in 1 episode
• Action Primitives — 1× in this paper · explained in 1 episode
• Agent Memory — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• OSWorld-Human: Benchmarking the Efficiency of Computer-Use Agents
• RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents
• OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
• Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V
• OmniParser for Pure Vision Based GUI Agent
• OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
• ReAct: Synergizing Reasoning and Acting in Language Models
• Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluation
• MemGPT: Towards LLMs as Operating Systems
• A-MEM: Agentic Memory for LLM Agents
• SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills
• Auto-scaling Continuous Memory for GUI Agent
• Hybrid Self-evolving Structured Memory for GUI Agents
• MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents
• FocusMem: Factorizing Content, Readout, and Trust in Latent GUI Memory
• UI-Mem: Self-Evolving Experience Memory for Online Reinforcement Learning in Mobile GUI Agents
• What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States
• Darwinian Memory: A Training-Free Self-Regulating Memory System for GUI Agent Evolution
• Executable Agentic Memory for GUI Agent
• VerificAgent: Domain-Specific Memory Verification for Scalable Oversight of Aligned Computer-Use Agents

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