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From the 2 of 14 linked papers with an AI index.

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cs.AI2026

OpenForgeRL: Train Harness-native Agents in Any Environment

Xiao Yu, Baolin Peng, Ruize Xu +7

Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems. While power…

cs.AI2026

Orchard: An Open-Source Agentic Modeling Framework

Baolin Peng, Wenlin Yao, Qianhui Wu +11

Agentic modeling aims to transform LLMs into autonomous agents capable of solving complex tasks through planning, reasoning, tool use, and multi-turn interaction with external envi…

cs.AI2026

Synthetic Computers at Scale for Long-Horizon Productivity Simulation

Tao Ge, Baolin Peng, Hao Cheng +1

Realistic long-horizon productivity work is strongly conditioned on user-specific computer environments, where much of the work context is stored and organized through directory st…

cs.AI2026

AutoSurfer -- Teaching Web Agents through Comprehensive Surfing, Learning, and Modeling

Fazle Elahi Faisal, Qianhui Wu, Baolin Peng +1

Recent advances in multimodal large language models (LLMs) have revolutionized web agents that can automate complex tasks on websites. However, their accuracy remains limited by th…

cs.AI2026

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

Reuben Tan, Baolin Peng, Zhengyuan Yang +16

Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally optimized using sparse, outcome-bas…

cs.AI2026

WebXSkill: Skill Learning for Autonomous Web Agents

Zhaoyang Wang, Qianhui Wu, Xuchao Zhang +12

Autonomous web agents powered by large language models (LLMs) have shown promise in completing complex browser tasks, yet they still struggle with long-horizon workflows. A key bot…