activity
20242026
collaborators

8 papers

cs.CV2026

Omni-Embed-Mini: Binding Modalities Without Forgetting via Dense Distillation

Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan, Sahal Shaji Mullappilly +2

Extending a text embedding model to new modalities typically degrades text retrieval quality, and existing omni-modal embedders compensate with multi-billion parameters. We present…

cs.CV2026

Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision

Hanoona Rasheed, Mohammed Irfan Kurpath, Bin Ren +3

Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision models. As these capabilitie…

cs.CV2026

MAviS: A Multimodal Conversational Assistant For Avian Species

Yevheniia Kryklyvets, Mohammed Irfan Kurpath, Sahal Shaji Mullappilly +5

Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monitoring. However, existing multimo…

cs.CV2026

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…

cs.CV2025

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…

cs.CL2025

A Culturally-diverse Multilingual Multimodal Video Benchmark & Model

Bhuiyan Sanjid Shafique, Ashmal Vayani, Muhammad Maaz +26

Large multimodal models (LMMs) have recently gained attention due to their effectiveness to understand and generate descriptions of visual content. Most existing LMMs are in Englis…

cs.CL2025

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…

cs.CV2024

BiMediX2: Bio-Medical EXpert LMM for Diverse Medical Modalities

Sahal Shaji Mullappilly, Mohammed Irfan Kurpath, Sara Pieri +8

We introduce BiMediX2, a bilingual (Arabic-English) Bio-Medical EXpert Large Multimodal Model that supports text-based and image-based medical interactions. It enables multi-turn c…