activity
20242026
most citedKimi K2.5: Visual Agentic Intelligence

2 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models

Xiyu Ren, Zhaowei Wang, Yiming Du +11

Memory is essential for large vision-language models (LVLMs) to handle long, multimodal interactions, with two method directions providing this capability: long-context LVLMs and m…

cs.CV2026

Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context

Zhaowei Wang, Lishu Luo, Haodong Duan +9

Long-context modeling is becoming a core capability of modern large vision-language models (LVLMs), enabling sustained context management across long-document understanding, video…

cs.CV2026

Can Retrieval Heads See Images? Multimodal Retrieval Heads in Long-Context Vision-Language Models

Aaron Branson Cigres Li, Zhaowei Wang, Yu Zhao +9

Large vision-language models increasingly rely on long-context modeling to reason over documents, hour-level videos, and long-horizon agent trajectories, requiring them to locate r…

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.LG2025

Loong: Synthesize Long Chain-of-Thoughts at Scale through Verifiers

Xingyue Huang, Rishabh, Gregor Franke +43

Recent advances in Large Language Models (LLMs) have shown that their reasoning capabilities can be significantly improved through Reinforcement Learning with Verifiable Reward (RL…

cs.CL2025

VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training

Jipeng Zhang, Kehao Miao, Renjie Pi +4

Reinforcement Fine-Tuning (RFT) with verifiable rewards has advanced large language models but remains underexplored for Vision-Language (VL) models. The Vision-Language Reward Mod…

cs.LG2025

PIPE: Physics-Informed Position Encoding for Alignment of Satellite Images and Time Series

Haobo Li, Eunseo Jung, Zixin Chen +4

Multimodal time series forecasting is foundational in various fields, such as utilizing satellite imagery and numerical data for predicting typhoons in climate science. However, ex…

cs.CL2024★ 2 cited

LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing

Jiangshu Du, Yibo Wang, Wenting Zhao +37

This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and ques…