16 citations · 36 across the 13 of their papers we have counts for
15 papers
VLZip: Unified Visual and Textual Compression for Interleaved Long-Context Modeling
Yuqi Zhang, Cheng Chen, Yuyu Guo +6
Vision Language Models (VLMs) face significant challenges with ultra-long, interleaved image-text sequences due to the quadratic complexity of self-attention. Current solutions eit…
Multimodal Continuous Reasoning via Asymmetric Mutual Variational Learning
Shijie Li, Yilin Gao, Siyuan Yang +7
Multimodal Large Language Models (MLLMs) are often constrained by a language-space bottleneck, forcing complex visual reasoning into discrete tokens which can lose perceptual nuanc…
Janus-LoRA: A Balanced Low-Rank Adaptation for Continual Learning
Cheng Chen, Pengpeng Zeng, Yuyu Guo +3
Low-Rank Adaptation (LoRA) has emerged as a promising paradigm for Continual Learning. It independently updates its low-rank factors ( and ), creating a composite update to t…
SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval
Wenjie Yang, Hang Yu, Yuyu Guo +1
In this work, we address the critical yet underexplored challenge of symmetric multimodal-to-multimodal (MM2MM) retrieval, where queries and contexts are interchangeable. Existing…
OpAgent: Operator Agent for Web Navigation
Yuyu Guo, Wenjie Yang, Siyuan Yang +12
To fulfill user instructions, autonomous web agents must contend with the inherent complexity and volatile nature of real-world websites. Conventional paradigms predominantly rely…
From One-to-One to Many-to-Many: Dynamic Cross-Layer Injection for Deep Vision-Language Fusion
Cheng Chen, Yuyu Guo, Pengpeng Zeng +4
Vision-Language Models (VLMs) create a severe visual feature bottleneck by using a crude, asymmetric connection that links only the output of the vision encoder to the input of the…
Local-Global Information Interaction Debiasing for Dynamic Scene Graph Generation
Xinyu Lyu, Jingwei Liu, Yuyu Guo +1
The task of dynamic scene graph generation (DynSGG) aims to generate scene graphs for given videos, which involves modeling the spatial-temporal information in the video. However,…
Informative Scene Graph Generation via Debiasing
Lianli Gao, Xinyu Lyu, Yuyu Guo +5
Scene graph generation aims to detect visual relationship triplets, (subject, predicate, object). Due to biases in data, current models tend to predict common predicates, e.g. "on"…
Learning To Generate Scene Graph from Head to Tail
Chaofan Zheng, Xinyu Lyu, Yuyu Guo +3
Scene Graph Generation (SGG) represents objects and their interactions with a graph structure. Recently, many works are devoted to solving the imbalanced problem in SGG. However, u…
Fine-Grained Predicates Learning for Scene Graph Generation
Xinyu Lyu, Lianli Gao, Yuyu Guo +4
The performance of current Scene Graph Generation models is severely hampered by some hard-to-distinguish predicates, e.g., "woman-on/standing on/walking on-beach" or "woman-near/l…
One-shot Scene Graph Generation
Yuyu Guo, Jingkuan Song, Lianli Gao +1
As a structured representation of the image content, the visual scene graph (visual relationship) acts as a bridge between computer vision and natural language processing. Existing…
Exploiting long-term temporal dynamics for video captioning
Yuyu Guo, Jingqiu Zhang, Lianli Gao
Automatically describing videos with natural language is a fundamental challenge for computer vision and natural language processing. Recently, progress in this problem has been ac…
Relation Regularized Scene Graph Generation
Yuyu Guo, Lianli Gao, Jingkuan Song +4
Scene graph generation (SGG) is built on top of detected objects to predict object pairwise visual relations for describing the image content abstraction. Existing works have revea…
From General to Specific: Informative Scene Graph Generation via Balance Adjustment
Yuyu Guo, Lianli Gao, Xuanhan Wang +5
The scene graph generation (SGG) task aims to detect visual relationship triplets, i.e., subject, predicate, object, in an image, providing a structural vision layout for scene und…
From Deterministic to Generative: Multi-Modal Stochastic RNNs for Video Captioning
Jingkuan Song, Yuyu Guo, Lianli Gao +3
Video captioning in essential is a complex natural process, which is affected by various uncertainties stemming from video content, subjective judgment, etc. In this paper we build…