9 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…
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…
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 +4
Multi-object tracking (MOT) has traditionally focused on estimating trajectories of all objects in a video, without selectively reasoning about user-specified targets under semanti…
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…