20 citations · 49 across the 22 of their papers we have counts for
23 papers
Latent Policy Steering: An Efficient and Flexible Framework for Cross-Embodiment Transfer
Yiqi Wang, Mrinal Verghese, Jeff Schneider
The performance of learned robot visuomotor policies depends heavily on the size and quality of their training data, yet collecting high-quality demonstrations remains costly for r…
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…
Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale
Ang Li, Ben Liu, Bin Han +215
Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…
FoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis
Ruihao Xu, Xingming Shui, Jingxuan Niu +4
As AI-powered compliance monitoring becomes increasingly important in public governance and industrial safety, the ability to provide verifiable evidence and traceable accountabili…
Sheet As Token: A Graph-Enhanced Representation for Multi-Sheet Spreadsheet Understanding
Yiming Lei, Yuhang Yao, Yujia Zhang +6
Workbook-scale spreadsheet understanding is increasingly important for language-model-based data analysis agents, but remains challenging because relevant information is often dist…
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…
Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization
Hao Luo, Ye Wang, Wanpeng Zhang +9
We introduce Being-H0.5, a foundational Vision-Language-Action (VLA) model designed for robust cross-embodiment generalization across diverse robotic platforms. While existing VLAs…
Flash-VStream: Efficient Real-Time Understanding for Long Video Streams
Haoji Zhang, Yiqin Wang, Yansong Tang +3
Benefiting from the advances in large language models and cross-modal alignment, existing multimodal large language models have achieved prominent performance in image and short vi…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…
Latent Policy Steering with Embodiment-Agnostic Pretrained World Models
Yiqi Wang, Mrinal Verghese, Jeff Schneider
The performance of learned robot visuomotor policies is heavily dependent on the size and quality of the training dataset. Although large-scale robot and human datasets are increas…
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…
Ponder & Press: Advancing Visual GUI Agent towards General Computer Control
Yiqin Wang, Haoji Zhang, Jingqi Tian +1
Most existing GUI agents typically depend on non-vision inputs like HTML source code or accessibility trees, limiting their flexibility across diverse software environments and pla…
InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning
Xiaotian Han, Yiren Jian, Xuefeng Hu +8
Pre-training on large-scale, high-quality datasets is crucial for enhancing the reasoning capabilities of Large Language Models (LLMs), especially in specialized domains such as ma…
Coarse Correspondences Boost Spatial-Temporal Reasoning in Multimodal Language Model
Benlin Liu, Yuhao Dong, Yiqin Wang +6
Multimodal language models (MLLMs) are increasingly being applied in real-world environments, necessitating their ability to interpret 3D spaces and comprehend temporal dynamics. C…
Hierarchical Memory for Long Video QA
Yiqin Wang, Haoji Zhang, Yansong Tang +4
This paper describes our champion solution to the LOVEU Challenge @ CVPR'24, Track 1 (Long Video VQA). Processing long sequences of visual tokens is computationally expensive and m…
Flash-VStream: Memory-Based Real-Time Understanding for Long Video Streams
Haoji Zhang, Yiqin Wang, Yansong Tang +4
Benefiting from the advancements in large language models and cross-modal alignment, existing multi-modal video understanding methods have achieved prominent performance in offline…
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
Haogeng Liu, Quanzeng You, Xiaotian Han +7
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intri…
Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning
Yiqi Wang, Wentao Chen, Xiaotian Han +7
Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large…
COCO is "ALL'' You Need for Visual Instruction Fine-tuning
Xiaotian Han, Yiqi Wang, Bohan Zhai +2
Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. Visual instruction fine-tuning (IFT) is a vital process for aligning M…
InfiMM-Eval: Complex Open-Ended Reasoning Evaluation For Multi-Modal Large Language Models
Xiaotian Han, Quanzeng You, Yongfei Liu +9
Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. These models not only excel in traditional vision-language tasks but a…
OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline
Xianda Guo, Chenming Zhang, Juntao Lu +5
Stereo matching aims to estimate the disparity between matching pixels in a stereo image pair, which is important to robotics, autonomous driving, and other computer vision tasks.…
Multi-Prompt with Depth Partitioned Cross-Modal Learning
Yingjie Tian, Yiqi Wang, Xianda Guo +2
In recent years, soft prompt learning methods have been proposed to fine-tune large-scale vision-language pre-trained models for various downstream tasks. These methods typically c…
Concatenated Attention Neural Network for Image Restoration
Tian YingJie, Wang YiQi, Yang LinRui +1
In this paper, we present a general framework for low-level vision tasks including image compression artifacts reduction and image denoising. Under this framework, a novel concaten…