4 citations · 11 across the 9 of their papers we have counts for
9 papers
SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation
Zhengbo Jiao, Yiming Cheng, Yilei Jiang +15
Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines construct training data, search…
Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria
Juanxi Tian, Fengyuan Liu, Jiaming Han +6
Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human judgment. Prevailing RLHF a…
Envision: Benchmarking Unified Understanding & Generation for Causal World Process Insights
Juanxi Tian, Siyuan Li, Conghui He +2
Current multimodal models aim to transcend the limitations of single-modality representations by unifying understanding and generation, often using text-to-image (T2I) tasks to cal…
Taming LLMs by Scaling Learning Rates with Gradient Grouping
Siyuan Li, Juanxi Tian, Zedong Wang +4
Training large language models (LLMs) poses challenges due to their massive scale and heterogeneous architectures. While adaptive optimizers like AdamW help address gradient variat…
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization
Siyuan Li, Luyuan Zhang, Zedong Wang +8
Masked Image Modeling (MIM) with Vector Quantization (VQ) has achieved great success in both self-supervised pre-training and image generation. However, most existing methods strug…
Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning
Siyuan Li, Juanxi Tian, Zedong Wang +6
This paper delves into the interplay between vision backbones and optimizers, unvealing an inter-dependent phenomenon termed \textit{\textbf{b}ackbone-\textbf{o}ptimizer \textbf{c}…
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Peng Xia, Ze Chen, Juanxi Tian +21
Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the…
Switch EMA: A Free Lunch for Better Flatness and Sharpness
Siyuan Li, Zicheng Liu, Juanxi Tian +9
Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DN…
OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning
Siyuan Li, Zedong Wang, Zicheng Liu +5
Mixup augmentation has emerged as a widely used technique for improving the generalization ability of deep neural networks (DNNs). However, the lack of standardized implementations…