59 citations · 375 across the 88 of their papers we have counts for
11 papers · 1 filter
EVE: Verifiable Self-Evolution of MLLMs via Executable Visual Transformations
Yongrui Heng, Chaoya Jiang, Han Yang +2
Self-evolution of multimodal large language models (MLLMs) remains a critical challenge: pseudo-label-based methods suffer from progressive quality degradation as model predictions…
Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling
Zhen Ye, Xu Tan, Aoxiong Yin +8
Joint audio-video generation models have shown that unified generation yields stronger cross-modal coherence than cascaded approaches. However, existing models couple modalities th…
From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models
Hongrui Jia, Chaoya Jiang, Yongrui Heng +2
As Large Multimodal Models (LMMs) scale up and reinforcement learning (RL) methods mature, LMMs have made notable progress in complex reasoning and decision making. Yet training st…
Mitigating Visual Context Degradation in Large Multimodal Models: A Training-Free Decoupled Agentic Framework
Hongrui Jia, Chaoya Jiang, Shikun Zhang +1
With the continuous expansion of Large Language Models (LLMs) and advances in reinforcement learning, LLMs have demonstrated exceptional reasoning capabilities, enabling them to ad…
VLM-R: Region Recognition, Reasoning, and Refinement for Enhanced Multimodal Chain-of-Thought
Chaoya Jiang, Yongrui Heng, Wei Ye +6
Recently, reasoning-based MLLMs have achieved a degree of success in generating long-form textual reasoning chains. However, they still struggle with complex tasks that necessitate…
SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization
Hongrui Jia, Chaoya Jiang, Haiyang Xu +6
As language models continue to scale, Large Language Models (LLMs) have exhibited emerging capabilities in In-Context Learning (ICL), enabling them to solve language tasks by prefi…
Efficient Vision-and-Language Pre-training with Text-Relevant Image Patch Selection
Wei Ye, Chaoya Jiang, Haiyang Xu +6
Vision Transformers (ViTs) have become increasingly popular in large-scale Vision and Language Pre-training (VLP) models. Although previous VLP research has demonstrated the effica…
Hallucination Augmented Contrastive Learning for Multimodal Large Language Model
Chaoya Jiang, Haiyang Xu, Mengfan Dong +7
Multi-modal large language models (MLLMs) have been shown to efficiently integrate natural language with visual information to handle multi-modal tasks. However, MLLMs still face a…
BUS:Efficient and Effective Vision-language Pre-training with Bottom-Up Patch Summarization
Chaoya Jiang, Haiyang Xu, Wei Ye +7
Vision Transformer (ViT) based Vision-Language Pre-training (VLP) models have demonstrated impressive performance in various tasks. However, the lengthy visual token sequences fed…
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
Haixin Wang, Xinlong Yang, Jianlong Chang +5
Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The c…
TRIPS: Efficient Vision-and-Language Pre-training with Text-Relevant Image Patch Selection
Chaoya Jiang, Haiyang Xu, Chenliang Li +5
Vision Transformers (ViTs) have been widely used in large-scale Vision and Language Pre-training (VLP) models. Though previous VLP works have proved the effectiveness of ViTs, they…