10 citations · 16 across the 16 of their papers we have counts for
16 papers
TimeThink: Reasoning with Time for Video LLMs
Handong Li, Longteng Guo, Zikang Liu +8
Video reasoning requires models to identify and verify temporally localized evidence within long video sequences. Recent Video Large Language Models (Video-LLMs) have shown promisi…
Semantic-Enriched Latent Visual Reasoning
Tianrun Xu, Yue Sun, Qixun Wang +8
Multimodal latent-space reasoning aims to replace explicit thinking with images by performing visual reasoning directly in a compact latent space. However, existing approaches larg…
Can MLLMs Reason Beyond Language? VisReason: A Comprehensive Benchmark for Vision-Centric Reasoning
Longteng Guo, Yifan Wang, Pengkang Huo +4
Recent multimodal large language models (MLLMs) achieve strong performance on visual reasoning benchmarks, yet it remains unclear to what extent such performance reflects reasoning…
M-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering
Jiatong Ma, Longteng Guo, Yuchen Liu +4
We present M-VQA, a novel knowledge-based Visual Question Answering (VQA) benchmark, to enhance the evaluation of multimodal large language models (MLLMs) in fine-grained multi…
AdaSpark: Adaptive Sparsity for Efficient Long-Video Understanding
Handong Li, Zikang Liu, Longteng Guo +10
Processing long-form videos with Video Large Language Models (Video-LLMs) is computationally prohibitive. Current efficiency methods often compromise fine-grained perception throug…
LaVi: Efficient Large Vision-Language Models via Internal Feature Modulation
Tongtian Yue, Longteng Guo, Yepeng Tang +4
Despite the impressive advancements of Large Vision-Language Models (LVLMs), existing approaches suffer from a fundamental bottleneck: inefficient visual-language integration. Curr…
Prefix Grouper: Efficient GRPO Training through Shared-Prefix Forward
Zikang Liu, Tongtian Yue, Yepeng Tang +5
Group Relative Policy Optimization (GRPO) enhances policy learning by computing gradients from relative comparisons among candidate outputs that share a common input prefix. Despit…
Efficient Motion-Aware Video MLLM
Zijia Zhao, Yuqi Huo, Tongtian Yue +5
Most current video MLLMs rely on uniform frame sampling and image-level encoders, resulting in inefficient data processing and limited motion awareness. To address these challenges…
ChatSearch: a Dataset and a Generative Retrieval Model for General Conversational Image Retrieval
Zijia Zhao, Longteng Guo, Tongtian Yue +5
In this paper, we investigate the task of general conversational image retrieval on open-domain images. The objective is to search for images based on interactive conversations bet…
Ada-K Routing: Boosting the Efficiency of MoE-based LLMs
Tongtian Yue, Longteng Guo, Jie Cheng +2
In the era of Large Language Models (LLMs), Mixture-of-Experts (MoE) architectures offer a promising approach to managing computational costs while scaling up model parameters. Con…
BrainGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training
Tongtian Yue, Xuange Gao, Shuning Xue +4
Electroencephalogram (EEG) signals are pivotal in providing insights into spontaneous brain activity, highlighting their significant importance in neuroscience research. However, t…
OneDiff: A Generalist Model for Image Difference Captioning
Erdong Hu, Longteng Guo, Tongtian Yue +3
In computer vision, Image Difference Captioning (IDC) is crucial for accurately describing variations between closely related images. Traditional IDC methods often rely on speciali…
Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs
Zijia Zhao, Haoyu Lu, Yuqi Huo +6
Video understanding is a crucial next step for multimodal large language models (MLLMs). Various benchmarks are introduced for better evaluating the MLLMs. Nevertheless, current vi…
VL-Mamba: Exploring State Space Models for Multimodal Learning
Yanyuan Qiao, Zheng Yu, Longteng Guo +5
Multimodal large language models (MLLMs) have attracted widespread interest and have rich applications. However, the inherent attention mechanism in its Transformer structure requi…
SC-Tune: Unleashing Self-Consistent Referential Comprehension in Large Vision Language Models
Tongtian Yue, Jie Cheng, Longteng Guo +6
Recent trends in Large Vision Language Models (LVLMs) research have been increasingly focusing on advancing beyond general image understanding towards more nuanced, object-level re…
Knowledge Condensation and Reasoning for Knowledge-based VQA
Dongze Hao, Jian Jia, Longteng Guo +8
Knowledge-based visual question answering (KB-VQA) is a challenging task, which requires the model to leverage external knowledge for comprehending and answering questions grounded…