10 citations · 22 across the 9 of their papers we have counts for
9 papers
Latent Chain-of-Thought for Visual Reasoning
Guohao Sun, Hang Hua, Jian Wang +5
Chain-of-thought (CoT) reasoning is critical for improving the interpretability and reliability of Large Vision-Language Models (LVLMs). However, existing training algorithms such…
Visual Self-Refinement for Autoregressive Models
Jiamian Wang, Ziqi Zhou, Chaithanya Kumar Mummadi +5
Autoregressive models excel in sequential modeling and have proven to be effective for vision-language data. However, the spatial nature of visual signals conflicts with the sequen…
X-CoT: Explainable Text-to-Video Retrieval via LLM-based Chain-of-Thought Reasoning
Prasanna Reddy Pulakurthi, Jiamian Wang, Majid Rabbani +3
Prevalent text-to-video retrieval systems mainly adopt embedding models for feature extraction and compute cosine similarities for ranking. However, this design presents two limita…
Shuffle PatchMix Augmentation with Confidence-Margin Weighted Pseudo-Labels for Enhanced Source-Free Domain Adaptation
Prasanna Reddy Pulakurthi, Majid Rabbani, Jamison Heard +3
This work investigates Source-Free Domain Adaptation (SFDA), where a model adapts to a target domain without access to source data. A new augmentation technique, Shuffle PatchMix (…
Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data
Prasanna Reddy Pulakurthi, Majid Rabbani, Celso M. de Melo +2
This paper introduces a novel dual-region augmentation approach designed to reduce reliance on large-scale labeled datasets while improving model robustness and adaptability across…
Re-Imagining Multimodal Instruction Tuning: A Representation View
Yiyang Liu, James Chenhao Liang, Ruixiang Tang +8
Multimodal instruction tuning has proven to be an effective strategy for achieving zero-shot generalization by fine-tuning pre-trained Large Multimodal Models (LMMs) with instructi…
AMD: Automatic Multi-step Distillation of Large-scale Vision Models
Cheng Han, Qifan Wang, Sohail A. Dianat +6
Transformer-based architectures have become the de-facto standard models for diverse vision tasks owing to their superior performance. As the size of the models continues to scale…
Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval
Jiamian Wang, Guohao Sun, Pichao Wang +5
The increasing prevalence of video clips has sparked growing interest in text-video retrieval. Recent advances focus on establishing a joint embedding space for text and video, rel…
Image Translation as Diffusion Visual Programmers
Cheng Han, James C. Liang, Qifan Wang +5
We introduce the novel Diffusion Visual Programmer (DVP), a neuro-symbolic image translation framework. Our proposed DVP seamlessly embeds a condition-flexible diffusion model with…