arXiv (All)
open access
Adaptive-Group Process Rewards for GUI Agents
Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process rewards offer a promising direction for credit assignment to intermediate actions; however, accurately evaluating an action requires identifying ev
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- GUI-PRA: Process Reward Agent for GUI Tasks#798645
- GUI-PRA: Process Reward Agent for GUI Tasks#797231
- SCA: Spatial Credit Assignment for Reinforcement Learning of GUI Agents#1132140
- Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning#124062
- GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness#1247297
Record · ID 1342920
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive