1 citations · 3 across the 7 of their papers we have counts for
10 papers
Test-Time Generalized Category Discovery
Shambhavi Mishra, Omprakash Chakraborty, Julio Silva-Rodriguez +3
Test-Time Adaptation (TTA) and Generalized Category Discovery (GCD) are traditionally treated as disjoint problems: the former adapts models to domain shift assuming all test class…
Continual Enterprise World Model Discovery in Dynamic Systems
Shambhavi Mishra, David Vazquez, Perouz Taslakian +3
In an enterprise system, updating one field can set another, create a record, or start an approval. These effects are produced by business rules that are not built into the platfor…
Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future Directions
Sarthak Kumar Maharana, Shambhavi Mishra, Yunbei Zhang +6
Deep neural nets achieve remarkable performance when training and test data share the same distribution, but this assumption frequently breaks in real-world deployment, where data…
AInstein: Can LLMs Solve Research Problems From Parametric Memory Alone?
Shambhavi Mishra, Gaurav Sahu, Marco Pedersoli +3
Can large language models solve AI research problems using only their parametric knowledge, without fine-tuning, retrieval, or other external aids? We introduce AInstein, a framewo…
Rendering-Aware Reinforcement Learning for Vector Graphics Generation
Juan A. Rodriguez, Haotian Zhang, Abhay Puri +12
Scalable Vector Graphics (SVG) offer a powerful format for representing visual designs as interpretable code. Recent advances in vision-language models (VLMs) have enabled high-qua…
Distilling Specialized Orders for Visual Generation
Rishav Pramanik, Amin Sghaier, Masih Aminbeidokhti +6
Autoregressive (AR) image generators are becoming increasingly popular due to their ability to produce high-quality images and their scalability. Typical AR models are locked onto…
AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding
Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang +19
Aligning visual features with language embeddings is a key challenge in vision-language models (VLMs). The performance of such models hinges on having a good connector that maps vi…
Unsupervised Object Discovery: A Comprehensive Survey and Unified Taxonomy
José-Fabian Villa-Vásquez, Marco Pedersoli
Unsupervised object discovery is commonly interpreted as the task of localizing and/or categorizing objects in visual data without the need for labeled examples. While current obje…
Masked Multi-Query Slot Attention for Unsupervised Object Discovery
Rishav Pramanik, José-Fabian Villa-Vásquez, Marco Pedersoli
Unsupervised object discovery is becoming an essential line of research for tackling recognition problems that require decomposing an image into entities, such as semantic segmenta…
An Attention Model for group-level emotion recognition
Aarush Gupta, Dakshit Agrawal, Hardik Chauhan +2
In this paper we propose a new approach for classifying the global emotion of images containing groups of people. To achieve this task, we consider two different and complementary…