activity
20152026
most citedVQA: Visual Question Answering

1.1k citations · 1.3k across the 33 of their papers we have counts for

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8 papers · 1 filter

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

Controlling Multimodal LLMs via Reward-guided Decoding

Oscar Mañas, Pierluca D'Oro, Koustuv Sinha +3

As Multimodal Large Language Models (MLLMs) gain widespread applicability, it is becoming increasingly desirable to adapt them for diverse user needs. In this paper, we study the a…

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

CulturalFrames: Assessing Cultural Expectation Alignment in Text-to-Image Models and Evaluation Metrics

Shravan Nayak, Mehar Bhatia, Xiaofeng Zhang +6

The increasing ubiquity of text-to-image (T2I) models as tools for visual content generation raises concerns about their ability to accurately represent diverse cultural contexts -…

cs.CV2025

Learning What Matters: Prioritized Concept Learning via Relative Error-driven Sample Selection

Shivam Chandhok, Qian Yang, Oscar Manas +3

Instruction tuning has been central to the success of recent vision-language models (VLMs), but it remains expensive-requiring large-scale datasets, high-quality annotations, and l…

cs.IR2025

REARANK: Reasoning Re-ranking Agent via Reinforcement Learning

Le Zhang, Bo Wang, Xipeng Qiu +2

We present REARANK, a large language model (LLM)-based listwise reasoning reranking agent. REARANK explicitly reasons before reranking, significantly improving both performance and…

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…