2 citations · 6 across the 11 of their papers we have counts for
15 papers
GaugeVLM: Structuring Spatial Supervision with Measured Geometric Interventions
Hongbo Wang, Zihan Lin, Wenkui Yang +5
Vision-language models (VLMs) can contradict themselves across views of the same spatial relation and fail to respond when that relation changes. Addressing these failures requires…
Benchmark Everything Everywhere All at Once
Shiyun Xiong, Dongming Wu, Peiwen Sun +5
Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit measures of performance. However, their construction is labor-intensiv…
BitLM: Unlocking Multi-Token Language Generation with Bitwise Continuous Diffusion
Shaobin Zhuang, Yuang Ai, Jiaming Han +7
Autoregressive language models generate text one token at a time, yet natural language is inherently structured in multi-token units, including phrases, n-grams, and collocations t…
BitDance: Scaling Autoregressive Generative Models with Binary Tokens
Yuang Ai, Jiaming Han, Shaobin Zhuang +8
We present BitDance, a scalable autoregressive (AR) image generator that predicts binary visual tokens instead of codebook indices. With high-entropy binary latents, BitDance lets…
UniWeTok: An Unified Binary Tokenizer with Codebook Size for Unified Multimodal Large Language Model
Shaobin Zhuang, Yuang Ai, Jiaming Han +12
Unified Multimodal Large Language Models (MLLMs) require a visual representation that simultaneously supports high-fidelity reconstruction, complex semantic extraction, and generat…
Random Wins All: Rethinking Grouping Strategies for Vision Tokens
Qihang Fan, Yuang Ai, Huaibo Huang +1
Since Transformers are introduced into vision architectures, their quadratic complexity has always been a significant issue that many research efforts aim to address. A representat…
Expand and Prune: Maximizing Trajectory Diversity for Effective GRPO in Generative Models
Shiran Ge, Chenyi Huang, Yuang Ai +3
Group Relative Policy Optimization (GRPO) is a powerful technique for aligning generative models, but its effectiveness is bottlenecked by the conflict between large group sizes an…
Rectifying Magnitude Neglect in Linear Attention
Qihang Fan, Huaibo Huang, Yuang Ai +1
As the core operator of Transformers, Softmax Attention exhibits excellent global modeling capabilities. However, its quadratic complexity limits its applicability to vision tasks.…
Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention
Yuang Ai
Transformer-based models have made remarkable progress in image restoration (IR) tasks. However, the quadratic complexity of self-attention in Transformer hinders its applicability…
DiCo: Revitalizing ConvNets for Scalable and Efficient Diffusion Modeling
Yuang Ai, Qihang Fan, Xuefeng Hu +3
Diffusion Transformer (DiT), a promising diffusion model for visual generation, demonstrates impressive performance but incurs significant computational overhead. Intriguingly, ana…
LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restoration
Yuang Ai, Huaibo Huang, Ran He
Prompt-based all-in-one image restoration (IR) frameworks have achieved remarkable performance by incorporating degradation-specific information into prompt modules. Nevertheless,…
DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation
Yuang Ai, Xiaoqiang Zhou, Huaibo Huang +4
Image restoration (IR) in real-world scenarios presents significant challenges due to the lack of high-capacity models and comprehensive datasets. To tackle these issues, we presen…
InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning
Xiaotian Han, Yiren Jian, Xuefeng Hu +8
Pre-training on large-scale, high-quality datasets is crucial for enhancing the reasoning capabilities of Large Language Models (LLMs), especially in specialized domains such as ma…
Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration
Yuang Ai, Huaibo Huang, Xiaoqiang Zhou +2
Despite substantial progress, all-in-one image restoration (IR) grapples with persistent challenges in handling intricate real-world degradations. This paper introduces MPerceiver:…
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer
Yuang Ai, Xiaoqiang Zhou, Huaibo Huang +2
Unsupervised Domain Adaptation (UDA) can effectively address domain gap issues in real-world image Super-Resolution (SR) by accessing both the source and target data. Considering p…