10 papers
MedCTA: A Benchmark for Clinical Tool Agents
Tajamul Ashraf, Hyewon Jeong, Fida Mohammad Thoker +1
To make clinically grounded decisions, medical AI agents are expected to go beyond simple recognition and be capable of tool retrieval, evidence acquisition, and integration. Exist…
CarePilot: A Multi-Agent Framework for Long-Horizon Computer Task Automation in Healthcare
Akash Ghosh, Tajamul Ashraf, Rishu Kumar Singh +4
Multimodal agentic pipelines are transforming human-computer interaction by enabling efficient and accessible automation of complex, real-world tasks. However, recent efforts have…
MedSPOT: A Workflow-Aware Sequential Grounding Benchmark for Clinical GUI
Rozain Shakeel, Abdul Rahman Mohammad Ali, Muneeb Mushtaq +2
Despite the rapid progress of Multimodal Large Language Models (MLLMs), their ability to perform reliable visual grounding in high-stakes clinical software environments remains und…
QTrack: Query-Driven Reasoning for Multi-modal MOT
Tajamul Ashraf, Tavaheed Tariq, Sonia Yadav +5
Category-level multi-object trackers estimate trajectories for all detected instances, whereas some applications require propagating only targets specified by a user. We study offl…
GroundedSurg: A Multi-Procedure Benchmark for Language-Conditioned Surgical Tool Segmentation
Tajamul Ashraf, Abrar Ul Riyaz, Wasif Tak +4
Clinically reliable perception of surgical scenes is essential for advancing intelligent, context-aware intraoperative assistance such as instrument handoff guidance, collision avo…
MATRIX: Multimodal Agent Tuning for Robust Tool-Use Reasoning
Tajamul Ashraf, Umair Nawaz, Abdelrahman M. Shaker +4
Vision language models (VLMs) are increasingly deployed as controllers with access to external tools for complex reasoning and decision-making, yet their effectiveness remains limi…
MIRA: A Novel Framework for Fusing Modalities in Medical RAG
Jinhong Wang, Tajamul Ashraf, Zongyan Han +2
Multimodal Large Language Models (MLLMs) have significantly advanced AI-assisted medical diagnosis, but they often generate factually inconsistent responses that deviate from estab…
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…
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…
D-MASTER: Mask Annealed Transformer for Unsupervised Domain Adaptation in Breast Cancer Detection from Mammograms
Tajamul Ashraf, Krithika Rangarajan, Mohit Gambhir +2
We focus on the problem of Unsupervised Domain Adaptation (\uda) for breast cancer detection from mammograms (BCDM) problem. Recent advancements have shown that masked image modeli…