activity
20232025
most citedBigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks

1 citations · 2 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CL2025

ColMate: Contrastive Late Interaction and Masked Text for Multimodal Document Retrieval

Ahmed Masry, Megh Thakkar, Patrice Bechard +9

Retrieval-augmented generation has proven practical when models require specialized knowledge or access to the latest data. However, existing methods for multimodal document retrie…

cs.LG2025★ 1 cited

Grounding Computer Use Agents on Human Demonstrations

Aarash Feizi, Shravan Nayak, Xiangru Jian +14

Building reliable computer-use agents requires grounding: accurately connecting natural language instructions to the correct on-screen elements. While large datasets exist for web…

cs.CL2025

DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture

Arijit Maji, Raghvendra Kumar, Akash Ghosh +6

We introduce DRISHTIKON, a first-of-its-kind multimodal and multilingual benchmark centered exclusively on Indian culture, designed to evaluate the cultural understanding of genera…

cs.CV2025

WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation

Rabiul Awal, Mahsa Massoud, Aarash Feizi +10

We present WebMMU, a multilingual benchmark that evaluates three core web tasks: (1) website visual question answering, (2) code editing involving HTML/CSS/JavaScript, and (3) mock…

cs.CV2025

The Promise of RL for Autoregressive Image Editing

Saba Ahmadi, Rabiul Awal, Ankur Sikarwar +8

While image generation techniques are now capable of producing high-quality images that respect prompts which span multiple sentences, the task of text-guided image editing remains…

cs.CV2025

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…

cs.CV2025

CTRL-O: Language-Controllable Object-Centric Visual Representation Learning

Aniket Didolkar, Andrii Zadaianchuk, Rabiul Awal +3

Object-centric representation learning aims to decompose visual scenes into fixed-size vectors called "slots" or "object files", where each slot captures a distinct object. Current…

cs.CV2025

UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction

Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin +11

Autonomous agents that navigate Graphical User Interfaces (GUIs) to automate tasks like document editing and file management can greatly enhance computer workflows. While existing…

cs.LG2024★ 1 cited

BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks

Juan Rodriguez, Xiangru Jian, Siba Smarak Panigrahi +40

Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and sum…

cs.LG2024

Introducing Milabench: Benchmarking Accelerators for AI

Pierre Delaunay, Xavier Bouthillier, Olivier Breuleux +12

AI workloads, particularly those driven by deep learning, are introducing novel usage patterns to high-performance computing (HPC) systems that are not comprehensively captured by…

cs.CV2024

Benchmarking Vision Language Models for Cultural Understanding

Shravan Nayak, Kanishk Jain, Rabiul Awal +5

Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their…

cs.CV2023

Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional Understanding

Le Zhang, Rabiul Awal, Aishwarya Agrawal

Vision-Language Models (VLMs), such as CLIP, exhibit strong image-text comprehension abilities, facilitating advances in several downstream tasks such as zero-shot image classifica…