289 citations · 655 across the 80 of their papers we have counts for
25 papers · 1 filter
A Benchmark for Omni-Modal Reasoning in Long Videos
Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan, Jinxing Zhou +12
Long-form omni-modal video understanding requires integrating vision, speech, and ambient audio with coherent long-context reasoning. Existing video benchmarks often trade off temp…
MedROV: Towards Real-Time Open-Vocabulary Detection Across Diverse Medical Imaging Modalities
Tooba Tehreem Sheikh, Jean Lahoud, Rao Muhammad Anwer +3
Traditional object detection models in medical imaging operate within a closed-set paradigm, limiting their ability to detect objects of novel labels. Open-vocabulary object detect…
EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards
Omkar Thawakar, Shravan Venkatraman, Ritesh Thawkar +5
Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines still depend on human-curated dat…
DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models
Komal Kumar, Rao Muhammad Anwer, Fahad Shahbaz Khan +3
Efficient fine-tuning of pre-trained Text-to-Image (T2I) models involves adjusting the model to suit a particular task or dataset while minimizing computational resources and limit…
How Good are Foundation Models in Step-by-Step Embodied Reasoning?
Dinura Dissanayake, Ahmed Heakl, Omkar Thawakar +9
Embodied agents operating in the physical world must make decisions that are not only effective but also safe, spatially coherent, and grounded in context. While recent advances in…
Beyond Simple Edits: Composed Video Retrieval with Dense Modifications
Omkar Thawakar, Dmitry Demidov, Ritesh Thawkar +4
Composed video retrieval is a challenging task that strives to retrieve a target video based on a query video and a textual description detailing specific modifications. Standard r…
Think Before You Segment: An Object-aware Reasoning Agent for Referring Audio-Visual Segmentation
Jinxing Zhou, Yanghao Zhou, Mingfei Han +4
Referring Audio-Visual Segmentation (Ref-AVS) aims to segment target objects in audible videos based on given reference expressions. Prior works typically rely on learning latent e…
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping
Dongming Wu, Yanping Fu, Saike Huang +8
General robotic grasping systems require accurate object affordance perception in diverse open-world scenarios following human instructions. However, current studies suffer from th…
All in One: Visual-Description-Guided Unified Point Cloud Segmentation
Zongyan Han, Mohamed El Amine Boudjoghra, Jiahua Dong +2
Unified segmentation of 3D point clouds is crucial for scene understanding, but is hindered by its sparse structure, limited annotations, and the challenge of distinguishing fine-g…
AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock
Umair Nawaz, Muhammad Zaigham Zaheer, Ufaq Khan +4
Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sectors face considerable challenge…
TerraFM: A Scalable Foundation Model for Unified Multisensor Earth Observation
Muhammad Sohail Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah +5
Modern Earth observation (EO) increasingly leverages deep learning to harness the scale and diversity of satellite imagery across sensors and regions. While recent foundation model…
TAViS: Text-bridged Audio-Visual Segmentation with Foundation Models
Ziyang Luo, Nian Liu, Xuguang Yang +5
Audio-Visual Segmentation (AVS) faces a fundamental challenge of effectively aligning audio and visual modalities. While recent approaches leverage foundation models to address dat…
Fann or Flop: A Multigenre, Multiera Benchmark for Arabic Poetry Understanding in LLMs
Wafa Alghallabi, Ritesh Thawkar, Sara Ghaboura +5
Arabic poetry is one of the richest and most culturally rooted forms of expression in the Arabic language, known for its layered meanings, stylistic diversity, and deep historical…
ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark
Sara Ghaboura, Ketan More, Wafa Alghallabi +5
As Large Multimodal Models (LMMs) become more capable, there is growing interest in evaluating their reasoning processes alongside their final outputs. However, most benchmarks rem…
Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks
Tajamul Ashraf, Amal Saqib, Hanan Ghani +11
Deep reasoning is fundamental for solving complex tasks, especially in vision-centric scenarios that demand sequential, multimodal understanding. However, existing benchmarks typic…
OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning
Zongyan Han, Jiale Cao, Shuo Chen +3
Open-Vocabulary Segmentation (OVS) has drawn increasing attention for its capacity to generalize segmentation beyond predefined categories. However, existing methods typically pred…
Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining
Qi Fan, Kaiqi Liu, Nian Liu +4
Cross-domain few-shot segmentation (CD-FSS) aims to segment objects of novel classes in new domains, which is often challenging due to the diverse characteristics of target domains…
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…
Tracking Meets Large Multimodal Models for Driving Scenario Understanding
Ayesha Ishaq, Jean Lahoud, Fahad Shahbaz Khan +3
Large Multimodal Models (LMMs) have recently gained prominence in autonomous driving research, showcasing promising capabilities across various emerging benchmarks. LMMs specifical…
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…
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…
CLIMB-3D: Continual Learning for Imbalanced 3D Instance Segmentation
Vishal Thengane, Jean Lahoud, Hisham Cholakkal +4
While 3D instance segmentation (3DIS) has advanced significantly, most existing methods assume that all object classes are known in advance and uniformly distributed. However, this…