33 citations · 133 across the 57 of their papers we have counts for
61 papers
DocAtlas: Multilingual Document Understanding Across 80+ Languages
Ahmed Heakl, Youssef Mohamed, Abdullah Sohail +6
Multilingual document understanding remains limited for low-resource languages due to scarce training data and model-based annotation pipelines that perpetuate existing biases. We…
Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework
Komal Kumar, Aman Chadha, Salman Khan +2
The rapid growth of scientific literature has made it increasingly difficult for researchers to efficiently discover, evaluate, and synthesize relevant work. Recent advances in mul…
MediX-R1: Open Ended Medical Reinforcement Learning
Sahal Shaji Mullappilly, Mohammed Irfan Kurpath, Omair Mohamed +5
We introduce MediX-R1, an open-ended Reinforcement Learning (RL) framework for medical multimodal large language models (MLLMs) that enables clinically grounded, free-form answers…
GenZSL: Generative Zero-Shot Learning Via Inductive Variational Autoencoder
Shiming Chen, Dingjie Fu, Salman Khan +1
Remarkable progress in zero-shot learning (ZSL) has been achieved using generative models. However, existing generative ZSL methods merely generate (imagine) the visual features fr…
ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Tasks
Akashah Shabbir, Muhammad Akhtar Munir, Akshay Dudhane +6
Recent progress in large language models (LLMs) has enabled tool-augmented agents capable of solving complex real-world tasks through step-by-step reasoning. However, existing eval…
Deep Learning in Concealed Dense Prediction
Pancheng Zhao, Deng-Ping Fan, Shupeng Cheng +5
Deep learning is developing rapidly and handling common computer vision tasks well. It is time to pay attention to more complex vision tasks, as model size, knowledge, and reasonin…
LLM Post-Training: A Deep Dive into Reasoning Large Language Models
Komal Kumar, Tajamul Ashraf, Omkar Thawakar +7
Large Language Models (LLMs) have transformed the natural language processing landscape and brought to life diverse applications. Pretraining on vast web-scale data has laid the fo…
How Good is my Histopathology Vision-Language Foundation Model? A Holistic Benchmark
Roba Al Majzoub, Hashmat Malik, Muzammal Naseer +4
Recently, histopathology vision-language foundation models (VLMs) have gained popularity due to their enhanced performance and generalizability across different downstream tasks. H…
DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model for Driving Scenario Understanding
Ayesha Ishaq, Jean Lahoud, Ketan More +10
While large multimodal models (LMMs) have demonstrated strong performance across various Visual Question Answering (VQA) tasks, certain challenges require complex multi-step reason…
LLMVoX: Autoregressive Streaming Text-to-Speech Model for Any LLM
Sambal Shikhar, Mohammed Irfan Kurpath, Sahal Shaji Mullappilly +5
Recent advancements in speech-to-speech dialogue systems leverage LLMs for multimodal interactions, yet they remain hindered by fine-tuning requirements, high computational overhea…
Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology
Hashmat Shadab Malik, Shahina Kunhimon, Muzammal Naseer +2
Adversarial attacks pose significant challenges for vision models in critical fields like healthcare, where reliability is essential. Although adversarial training has been well st…
C-Drag: Chain-of-Thought Driven Motion Controller for Video Generation
Yuhao Li, Mirana Claire Angel, Salman Khan +4
Trajectory-based motion control has emerged as an intuitive and efficient approach for controllable video generation. However, the existing trajectory-based approaches are usually…
AirCast: Improving Air Pollution Forecasting Through Multi-Variable Data Alignment
Vishal Nedungadi, Muhammad Akhtar Munir, Marc Rußwurm +5
Air pollution remains a leading global health risk, exacerbated by rapid industrialization and urbanization, contributing significantly to morbidity and mortality rates. In this pa…
Time Travel: A Comprehensive Benchmark to Evaluate LMMs on Historical and Cultural Artifacts
Sara Ghaboura, Ketan More, Ritesh Thawkar +6
Understanding historical and cultural artifacts demands human expertise and advanced computational techniques, yet the process remains complex and time-intensive. While large multi…
AIN: The Arabic INclusive Large Multimodal Model
Ahmed Heakl, Sara Ghaboura, Omkar Thawkar +4
Amid the swift progress of large language models (LLMs) and their evolution into large multimodal models (LMMs), significant strides have been made in high-resource languages such…
Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language Models
Hashmat Shadab Malik, Fahad Shamshad, Muzammal Naseer +3
Multi-modal Large Language Models (MLLMs) excel in vision-language tasks but remain vulnerable to visual adversarial perturbations that can induce hallucinations, manipulate respon…
GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing
Akashah Shabbir, Mohammed Zumri, Mohammed Bennamoun +2
Recent advances in large multimodal models (LMMs) have recognized fine-grained grounding as an imperative factor of visual understanding and dialogue. However, the benefits of such…
Discriminative Image Generation with Diffusion Models for Zero-Shot Learning
Dingjie Fu, Wenjin Hou, Shiming Chen +4
Generative Zero-Shot Learning (ZSL) methods synthesize class-related features based on predefined class semantic prototypes, showcasing superior performance. However, this feature…
UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities
Muhammad Uzair Khattak, Shahina Kunhimon, Muzammal Naseer +2
Vision-Language Models (VLMs) trained via contrastive learning have achieved notable success in natural image tasks. However, their application in the medical domain remains limite…
EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues
Sagar Soni, Akshay Dudhane, Hiyam Debary +8
Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and {r…
GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks
Muhammad Sohail Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah +5
While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they do not effectively address the specific challenges of geospatial applications. Gene…
VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos
Shehan Munasinghe, Hanan Gani, Wenqi Zhu +4
Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle bas…
CAMEL-Bench: A Comprehensive Arabic LMM Benchmark
Sara Ghaboura, Ahmed Heakl, Omkar Thawakar +7
Recent years have witnessed a significant interest in developing large multimodal models (LMMs) capable of performing various visual reasoning and understanding tasks. This has led…
How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization?
Jiahua Dong, Wenqi Liang, Hongliu Li +5
Custom diffusion models (CDMs) have attracted widespread attention due to their astonishing generative ability for personalized concepts. However, most existing CDMs unreasonably a…