14 citations · 80 across the 27 of their papers we have counts for
17 papers · 1 filter
Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs
Chenhong He, Lei Li, Shicheng Li +5
Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a satisfactory hybrid design, with no consensus on why certain attention patterns w…
RICO: Improving Accuracy and Completeness in Image Recaptioning via Visual Reconstruction
Yuchi Wang, Yishuo Cai, Shuhuai Ren +6
Image recaptioning is widely used to generate training datasets with enhanced quality for various multimodal tasks. Existing recaptioning methods typically rely on powerful multimo…
TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming Videos
Linli Yao, Yicheng Li, Yuancheng Wei +11
The rapid growth of online video platforms, particularly live streaming services, has created an urgent need for real-time video understanding systems. These systems must process c…
TEMPLE: Incentivizing Temporal Understanding of Video Large Language Models via Progressive Pre-SFT Alignment
Shicheng Li, Lei Li, Kun Ouyang +7
Video Large Language Models (Video LLMs) have achieved significant success by adopting the paradigm of large-scale pre-training followed by supervised fine-tuning (SFT). However, e…
Next Block Prediction: Video Generation via Semi-Autoregressive Modeling
Shuhuai Ren, Shuming Ma, Xu Sun +1
Next-Token Prediction (NTP) is a de facto approach for autoregressive (AR) video generation, but it suffers from suboptimal unidirectional dependencies and slow inference speed. In…
DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models
Linli Yao, Lei Li, Shuhuai Ren +4
The visual projector, which bridges the vision and language modalities and facilitates cross-modal alignment, serves as a crucial component in MLLMs. However, measuring the effecti…
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Chaoyou Fu, Yuhan Dai, Yongdong Luo +18
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus rem…
Towards Multimodal Video Paragraph Captioning Models Robust to Missing Modality
Sishuo Chen, Lei Li, Shuhuai Ren +5
Video paragraph captioning (VPC) involves generating detailed narratives for long videos, utilizing supportive modalities such as speech and event boundaries. However, the existing…
TempCompass: Do Video LLMs Really Understand Videos?
Yuanxin Liu, Shicheng Li, Yi Liu +6
Recently, there is a surge in interest surrounding video large language models (Video LLMs). However, existing benchmarks fail to provide a comprehensive feedback on the temporal p…
FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation
Yuanxin Liu, Lei Li, Shuhuai Ren +5
Recently, open-domain text-to-video (T2V) generation models have made remarkable progress. However, the promising results are mainly shown by the qualitative cases of generated vid…
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding
Shuhuai Ren, Linli Yao, Shicheng Li +2
This work proposes TimeChat, a time-sensitive multimodal large language model specifically designed for long video understanding. Our model incorporates two key architectural contr…
VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models
Shicheng Li, Lei Li, Shuhuai Ren +5
The ability to perceive how objects change over time is a crucial ingredient in human intelligence. However, current benchmarks cannot faithfully reflect the temporal understanding…
TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding
Shuhuai Ren, Sishuo Chen, Shicheng Li +2
Large-scale video-language pre-training has made remarkable strides in advancing video-language understanding tasks. However, the heavy computational burden of video encoding remai…
MIT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning
Lei Li, Yuwei Yin, Shicheng Li +9
Instruction tuning has significantly advanced large language models (LLMs) such as ChatGPT, enabling them to align with human instructions across diverse tasks. However, progress i…
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
Shuhuai Ren, Aston Zhang, Yi Zhu +5
This work proposes POMP, a prompt pre-training method for vision-language models. Being memory and computation efficient, POMP enables the learned prompt to condense semantic infor…
Delving into the Openness of CLIP
Shuhuai Ren, Lei Li, Xuancheng Ren +2
Contrastive Language-Image Pre-training (CLIP) formulates image classification as an image-to-text matching task, i.e., matching images to the corresponding natural language descri…
DCA: Diversified Co-Attention towards Informative Live Video Commenting
Zhihan Zhang, Zhiyi Yin, Shuhuai Ren +2
We focus on the task of Automatic Live Video Commenting (ALVC), which aims to generate real-time video comments with both video frames and other viewers' comments as inputs. A majo…