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20242026
most citedKimi K2.5: Visual Agentic Intelligence

2 citations · 3 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

VGIF-Score: Interpretable and Diagnostic Evaluation of Spatio-Temporal Instruction Following in Video Generation

Songyu Xu, Xin Wang, Qiang Chen +6

Recent video generation models (VGMs) have made substantial progress in visual fidelity, yet their ability to follow long, compositional instructions remains insufficiently evaluat…

cs.CV2026

Kwai Keye-VL-2.0 Technical Report

Kwai Keye Team, Bin Wen, Changyi Liu +50

We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding and agentic intelligence. To…

cs.CV2026

DetailVerifyBench: A Benchmark for Dense Hallucination Localization in Long Image Captions

Xinran Wang, Yuxuan Zhang, Xiao Zhang +7

Accurately detecting and localizing hallucinations is a critical task for ensuring high reliability of image captions. In the era of Multimodal Large Language Models (MLLMs), capti…

cs.CV2026

Hepato-LLaVA: An Expert MLLM with Sparse Topo-Pack Attention for Hepatocellular Pathology Analysis on Whole Slide Images

Yuxuan Yang, Zhonghao Yan, Yi Zhang +6

Hepatocellular Carcinoma diagnosis relies heavily on the interpretation of gigapixel Whole Slide Images. However, current computational approaches are constrained by fixed-resoluti…

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.LG2026

Entropy-Adaptive Fine-Tuning: Resolving Confident Conflicts to Mitigate Forgetting

Muxi Diao, Lele Yang, Wuxuan Gong +6

Supervised Fine-Tuning (SFT) is the standard paradigm for domain adaptation, yet it frequently incurs the cost of catastrophic forgetting. In sharp contrast, on-policy Reinforcemen…