8 citations · 12 across the 18 of their papers we have counts for
11 papers · 1 filter
Ablate-to-Validate: Are Vision-Language Models Really Using Continuous Thought Tokens?
Tianyi Zhang, Mahtab Bigverdi, Ranjay Krishna
Vision-language models (VLMs) are increasingly augmented with continuous or latent non-textual tokens intended to support "visual thinking." Despite improved task accuracy, this al…
RefDecoder: Enhancing Visual Generation with Conditional Video Decoding
Xiang Fan, Yuheng Wang, Bohan Fang +2
Video generation powers a vast array of downstream applications. However, while the de facto standard, i.e., latent diffusion models, typically employ heavily conditioned denoising…
Posterior Augmented Flow Matching
George Stoica, Sayak Paul, Matthew Wallingford +6
Flow matching (FM) trains a time-dependent vector field that transports samples from a simple prior to a complex data distribution. However, for high-dimensional images, each train…
ThinkMorph: Emergent Properties in Multimodal Interleaved Chain-of-Thought Reasoning
Jiawei Gu, Yunzhuo Hao, Huichen Will Wang +5
Multimodal reasoning requires iterative coordination between language and vision, yet it remains unclear what constitutes a meaningful interleaved chain of thought. We posit that t…
Synthetic Visual Genome
Jae Sung Park, Zixian Ma, Linjie Li +9
Reasoning over visual relationships-spatial, functional, interactional, social, etc.-is considered to be a fundamental component of human cognition. Yet, despite the major advances…
FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations
Cheng-Yu Hsieh, Pavan Kumar Anasosalu Vasu, Fartash Faghri +5
Visual understanding is inherently contextual -- what we focus on in an image depends on the task at hand. For instance, given an image of a person holding a bouquet of flowers, we…
REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations
Peter Sushko, Ayana Bharadwaj, Zhi Yang Lim +6
Existing image editing models struggle to meet real-world demands. Despite excelling in academic benchmarks, they have yet to be widely adopted for real user needs. Datasets that p…
Perception Tokens Enhance Visual Reasoning in Multimodal Language Models
Mahtab Bigverdi, Zelun Luo, Cheng-Yu Hsieh +4
Multimodal language models (MLMs) still face challenges in fundamental visual perception tasks where specialized models excel. Tasks requiring reasoning about 3D structures benefit…
NVILA: Efficient Frontier Visual Language Models
Zhijian Liu, Ligeng Zhu, Baifeng Shi +24
Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a…
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models
Matt Deitke, Christopher Clark, Sangho Lee +47
Today's most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good perfor…
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions
Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh +7
Humans describe complex scenes with compositionality, using simple text descriptions enriched with links and relationships. While vision-language research has aimed to develop mode…