1 citations · 1 across the 12 of their papers we have counts for
14 papers
StreamFlow: Dynamic Memory Flows for Streaming Video Understanding
Muxin Fu, Yifan Zhang, Wentao Zhang +5
Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under strict causality and bounded…
WorkDrive: Roadwork Chain of Causation for Autonomous Driving
Tianyi Jiang, Wen Zhang, Sihan Yang +2
Autonomous driving vision-language models (VLMs) struggle in roadwork zones, where familiar visual cues such as lane markings and permanent signs are altered or absent, and tempora…
SteerVTE: Seamless Video Text Editing with Style and Glyph Control
Kai Zeng, Moran Li, Zhengwei Wang +6
Visual text editing aims to precisely modify text in images and videos while preserving stylistic consistency and visual realism. Despite significant advances in the image domain,…
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-AI, Anyi Xu, Bangcai Lin +315
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…
PEARL: Personalized Streaming Video Understanding Model
Yuanhong Zheng, Ruichuan An, Xiaopeng Lin +10
Human cognition of new concepts is inherently a streaming process: we continuously recognize new objects or identities and update our memories over time. However, current multimoda…
GENIUS: Generative Fluid Intelligence Evaluation Suite
Ruichuan An, Sihan Yang, Ziyu Guo +8
Unified Multimodal Models (UMMs) have shown remarkable progress in visual generation. Yet, existing benchmarks predominantly assess , which reli…
AD-MIR: Bridging the Gap from Perception to Persuasion in Advertising Video Understanding via Structured Reasoning
Binxiao Xu, Junyu Feng, Xiaopeng Lin +7
Multimodal understanding of advertising videos is essential for interpreting the intricate relationship between visual storytelling and abstract persuasion strategies. However, des…
M2A: Multimodal Memory Agent with Dual-Layer Hybrid Memory for Long-Term Personalized Interactions
Junyu Feng, Binxiao Xu, Jiayi Chen +8
This work addresses the challenge of personalized question answering in long-term human-machine interactions: when conversational history spans weeks or months and exceeds the cont…
VCU-Bridge: Hierarchical Visual Connotation Understanding via Semantic Bridging
Ming Zhong, Yuanlei Wang, Liuzhou Zhang +6
While Multimodal Large Language Models (MLLMs) excel on benchmarks, their processing paradigm differs from the human ability to integrate visual information. Unlike humans who natu…
Jarvis: Towards Personalized AI Assistant via Personal KV-Cache Retrieval
Binxiao Xu, Junyu Feng, Shaolin Lu +5
The rapid development of Vision-language models (VLMs) enables open-ended perception and reasoning. Recent works have started to investigate how to adapt general-purpose VLMs into…
Small-Large Collaboration: Training-efficient Concept Personalization for Large VLM using a Meta Personalized Small VLM
Sihan Yang, Huitong Ji, Shaolin Lu +6
Personalizing Vision-Language Models (VLMs) to transform them into daily assistants has emerged as a trending research direction. However, leading companies like OpenAI continue to…
Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos
Weifeng Lin, Xinyu Wei, Ruichuan An +7
We present Perceive Anything Model (PAM), a conceptually straightforward and efficient framework for comprehensive region-level visual understanding in images and videos. Our appro…
UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens
Ruichuan An, Sihan Yang, Renrui Zhang +10
Personalized models have demonstrated remarkable success in understanding and generating concepts provided by users. However, existing methods use separate concept tokens for under…
Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMs
Ruichuan An, Kai Zeng, Ming Lu +5
Vision-Language Models (VLMs) have demonstrated exceptional performance in various multi-modal tasks. Recently, there has been an increasing interest in improving the personalizati…