activity
20242026
most citedInternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

4 citations · 5 across the 13 of their papers we have counts for

collaborators
Showing cs.AIShow all

8 papers · 1 filter

cs.AI2026

AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities

Kai Chen, Zichen Ding, Jiaye Ge +20

As Large Language Models (LLMs) evolve into autonomous agents, the need for unified evaluation infrastructure becomes critical. However, current evaluation pipelines remain highly…

cs.AI2026

MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop

Yikun Fu, Bowen Fu, Zhenyu Wu +10

Computer use agents (CUAs) have advanced rapidly in desktop automation, and a growing number of users deploy CUAs such as OpenClaw on Mac Mini for always-on automation. However, ex…

cs.AI2026

AlloSpatial: Agentic Harness Framework for Spatial Reasoning in Foundation Models

Shouwei Ruan, Bin Wang, Zhenyu Wu +5

Multimodal Foundation Models (MFMs) have made substantial progress, yet remain fragile in spatial reasoning over the physical world. A key bottleneck lies in their inability to tra…

cs.AI2026

OS-Themis: A Scalable Critic Framework for Generalist GUI Rewards

Zehao Li, Zhenyu Wu, Yibo Zhao +11

Reinforcement Learning (RL) has the potential to improve the robustness of GUI agents in stochastic environments, yet training is highly sensitive to the quality of the reward func…

cs.AI2026

World2Mind: Cognition Toolkit for Allocentric Spatial Reasoning in Foundation Models

Shouwei Ruan, Bin Wang, Zhenyu Wu +4

Achieving robust spatial reasoning remains a fundamental challenge for current Multimodal Foundation Models (MFMs). Existing methods either overfit statistical shortcuts via 3D gro…

cs.AI2025

OS-Oracle: A Comprehensive Framework for Cross-Platform GUI Critic Models

Zhenyu Wu, Jingjing Xie, Zehao Li +8

With VLM-powered computer-using agents (CUAs) becoming increasingly capable at graphical user interface (GUI) navigation and manipulation, reliable step-level decision-making has e…