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cs.AI2026

StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents

Haojie Hao, Longkun Hao, Yihang Lou +8

Reinforcement Learning (RL) has become a promising approach for improving GUI Agents in long-horizon, stochastic digital environments, but trajectory-level success feedback is too…

cs.AI2026

Automating Skill Acquisition through Large-Scale Mining of Open-Source Agentic Repositories: A Framework for Multi-Agent Procedural Knowledge Extraction

Shuzhen Bi, Mengsong Wu, Hao Hao +5

The transition from monolithic large language models (LLMs) to modular, skill-equipped agents represents a fundamental architectural shift in artificial intelligence deployment. Wh…

cs.AI2026

Scaling Laws for Educational AI Agents

Mengsong Wu, Hao Hao, Shuzhen Bi +5

While scaling laws for Large Language Models (LLMs) have been extensively studied along dimensions of model parameters, training data, and compute, the scaling behavior of LLM-base…

cs.AI2026

See and Remember: A Multimodal Agent for Web Traversal

Xinjun Wang, Shengyao Wang, Aimin Zhou +1

Autonomous web navigation requires agents to perceive complex visual environments and maintain long-term context, yet current Large Language Model (LLM) based agents often struggle…

cs.AI2025

SID: Benchmarking Guided Instruction Capabilities in STEM Education with a Socratic Interdisciplinary Dialogues Dataset

Mei Jiang, Houping Yue, Bingdong Li +4

Fostering students' abilities for knowledge integration and transfer in complex problem-solving scenarios is a core objective of modern education, and interdisciplinary STEM is a k…