most citedKimi K2.5: Visual Agentic Intelligence

2 citations · 3 across the 6 of their papers we have counts for

collaborators

8 papers

cs.LG2026

AdaptArena: Evaluating Test-Time Personalization of Web Agents

Dongchan Shin, Xing Han Lù, Jiaqi Deng +7

Large language model (LLM) agents have demonstrated strong performance on complex web navigation tasks, yet they remain brittle in real-world settings where user intentions are und…

cs.CL2026

Kimi K3: Open Frontier Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +398

We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…

cs.AI2026

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks

Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong +33

Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of f…

cs.AI2026

Beyond Forecasting: The Belief-to-Trade Layer in Prediction-Market Agents

Yishu Wang, Yuxuan Wang, Jiaqi Deng +1

Forecasting future events has attracted growing attention as a testbed for general-purpose AI. A natural way to ground this evaluation is let the models trade in the prediction mar…

cs.CL2026★ 2 cited

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +333

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.AI2025

OpenCUA: Open Foundations for Computer-Use Agents

Xinyuan Wang, Bowen Wang, Dunjie Lu +39

Vision-language models have demonstrated impressive capabilities as computer-use agents (CUAs) capable of automating diverse computer tasks. As their commercial potential grows, cr…

cs.AI2025

Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis

Tianbao Xie, Jiaqi Deng, Xiaochuan Li +12

Graphical user interface (GUI) grounding, the ability to map natural language instructions to specific actions on graphical user interfaces, remains a critical bottleneck in comput…

cs.CV2025★ 1 cited

Kimi-VL Technical Report

Kimi Team, Angang Du, Bohong Yin +92

We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…