1 citations · 2 across the 9 of their papers we have counts for
12 papers
EventLens: Event-Structure Reinforcement Learning for Video Understanding
Guowen Zhang, Boshen Xu, Zihao Yue +6
Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure that makes a video coherent. Th…
Grounding with Confidence: Controllable Generative Video Temporal Grounding
Jinhao Chen, Benlei Cui, Ruijian Jia +7
Video temporal grounding supports applications such as video search, content review, and automated editing by localizing events described in natural language. Yet existing generati…
Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety
Ting Ma, Xiufeng Huang, Benlei Cui +43
As large language models are increasingly deployed in real-world systems, safety failures can still lead to harmful outputs and dangerous misuse. We argue that the essence of safet…
Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety
Shikai Qiu, Xiaowen Xu, Benlei Cui +55
General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversarial nature of content and AI s…
MoCha:End-to-End Video Character Replacement without Structural Guidance
Zhengbo Xu, Jie Ma, Ziheng Wang +3
Controllable video character replacement with a user-provided identity remains a challenging problem due to the lack of paired video data. Prior works have predominantly relied on…
UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision
Ruiyan Han, Zhen Fang, XinYu Sun +9
While Unified Multimodal Models (UMMs) have achieved remarkable success in cross-modal comprehension, a significant gap persists in their ability to leverage such internal knowledg…
Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
Ye Wang, Ziheng Wang, Boshen Xu +14
Temporal Video Grounding (TVG), the task of locating specific video segments based on language queries, is a core challenge in long-form video understanding. While recent Large Vis…
Do Egocentric Video-Language Models Truly Understand Hand-Object Interactions?
Boshen Xu, Ziheng Wang, Yang Du +3
Egocentric video-language pretraining is a crucial step in advancing the understanding of hand-object interactions in first-person scenarios. Despite successes on existing testbeds…
Synchronized Video Storytelling: Generating Video Narrations with Structured Storyline
Dingyi Yang, Chunru Zhan, Ziheng Wang +4
Video storytelling is engaging multimedia content that utilizes video and its accompanying narration to attract the audience, where a key challenge is creating narrations for recor…
Movie101v2: Improved Movie Narration Benchmark
Zihao Yue, Yepeng Zhang, Ziheng Wang +1
Automatic movie narration aims to generate video-aligned plot descriptions to assist visually impaired audiences. Unlike standard video captioning, it involves not only describing…
An Efficient Sparse Inference Software Accelerator for Transformer-based Language Models on CPUs
Haihao Shen, Hengyu Meng, Bo Dong +9
In recent years, Transformer-based language models have become the standard approach for natural language processing tasks. However, stringent throughput and latency requirements i…
Edit As You Wish: Video Caption Editing with Multi-grained User Control
Linli Yao, Yuanmeng Zhang, Ziheng Wang +5
Automatically narrating videos in natural language complying with user requests, i.e. Controllable Video Captioning task, can help people manage massive videos with desired intenti…