1 citations · 1 across the 4 of their papers we have counts for
4 papers
No Hard Negatives Required: Concept Centric Learning Leads to Compositionality without Degrading Zero-shot Capabilities of Contrastive Models
Hai X. Pham, David T. Hoffmann, Ricardo Guerrero +1
Contrastive vision-language (V&L) models remain a popular choice for various applications. However, several limitations have emerged, most notably the limited ability of V&L models…
FAM Diffusion: Frequency and Attention Modulation for High-Resolution Image Generation with Stable Diffusion
Haosen Yang, Adrian Bulat, Isma Hadji +4
Diffusion models are proficient at generating high-quality images. They are however effective only when operating at the resolution used during training. Inference at a scaled reso…
Graph Guided Question Answer Generation for Procedural Question-Answering
Hai X. Pham, Isma Hadji, Xinnuo Xu +6
In this paper, we focus on task-specific question answering (QA). To this end, we introduce a method for generating exhaustive and high-quality training data, which allows us to tr…
Graph2Vid: Flow graph to Video Grounding for Weakly-supervised Multi-Step Localization
Nikita Dvornik, Isma Hadji, Hai Pham +4
In this work, we consider the problem of weakly-supervised multi-step localization in instructional videos. An established approach to this problem is to rely on a given list of st…