activity
20232026
most citedRethinking Patch Dependence for Masked Autoencoders

3 citations · 12 across the 15 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.LG2025

ThreadWeaver: Adaptive Threading for Efficient Parallel Reasoning in Language Models

Long Lian, Sida Wang, Felix Juefei-Xu +7

Scaling inference-time computation has enabled Large Language Models (LLMs) to achieve strong reasoning performance, but their inherently sequential decoding incurs substantial lat…

cs.CV2025

Pillar-0: A New Frontier for Radiology Foundation Models

Kumar Krishna Agrawal, Longchao Liu, Long Lian +11

Radiology plays an integral role in modern medicine, yet rising imaging volumes have far outpaced workforce growth. Foundation models offer a path toward assisting with the full sp…

cs.CV2025

Constantly Improving Image Models Need Constantly Improving Benchmarks

Jiaxin Ge, Grace Luo, Heekyung Lee +7

Recent advances in image generation, often driven by proprietary systems like GPT-4o Image Gen, regularly introduce new capabilities that reshape how users interact with these mode…

cs.CV2025

Describe Anything: Detailed Localized Image and Video Captioning

Long Lian, Yifan Ding, Yunhao Ge +8

Generating detailed and accurate descriptions for specific regions in images and videos remains a fundamental challenge for vision-language models. We introduce the Describe Anythi…

cs.CV2025

TULIP: Towards Unified Language-Image Pretraining

Zineng Tang, Long Lian, Seun Eisape +6

Despite the recent success of image-text contrastive models like CLIP and SigLIP, these models often struggle with vision-centric tasks that demand high-fidelity image understandin…

cs.AI2025

Learning Adaptive Parallel Reasoning with Language Models

Jiayi Pan, Xiuyu Li, Long Lian +6

Scaling inference-time computation has substantially improved the reasoning capabilities of language models. However, existing methods have significant limitations: serialized chai…

cs.CV2025★ 1 cited

Atlas: Multi-Scale Attention Improves Long Context Image Modeling

Kumar Krishna Agrawal, Long Lian, Longchao Liu +6

Efficiently modeling massive images is a long-standing challenge in machine learning. To this end, we introduce Multi-Scale Attention (MSA). MSA relies on two key ideas, (i) multi-…