collaborators

23 papers

cs.CL2026

GUI-Primitives: Diagnosing Spatial Reasoning Failures in Vision-Language GUI Grounding

Md Abrar Jahin, Md Rizwan Parvez

Computer-use agents ground natural-language instructions in screenshots to locate interface elements, yet existing benchmarks do not isolate whether models bind relational language…

cs.CL2026

A Survey on Agentic Security: Applications, Threats and Defenses

Asif Shahriar, Md Nafiu Rahman, Sadif Ahmed +2

LLM-based agents are now used throughout cybersecurity. While these agents facilitate powerful and autonomous security applications, their autonomy opens up new attack surfaces, an…

cs.CL2026

Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient LLM Reasoning

Raman Saparkhan, Majd Hawasly, Md Rizwan Parvez +1

Self-consistency (SC) is a popular technique for improving the reasoning accuracy of large language models by aggregating multiple sampled outputs, but it comes at a high computati…

cs.CR2026

Poison with Style: A Practical Poisoning Attack on Code Large Language Models

Khang Tran, Yazan Boshmaf, Issa Khalil +3

Code Large Language Models (CLLMs) serve as the core of modern code agents, enabling developers to automate complex software development tasks. In this paper, we present Poison-wit…

cs.CV2026

TimeSpot: Benchmarking Geo-Temporal Understanding in Vision-Language Models in Real-World Settings

Azmine Toushik Wasi, Shahriyar Zaman Ridoy, Koushik Ahamed Tonmoy +5

Geo-temporal understanding, the ability to infer location, time, and contextual properties from visual input alone, underpins applications such as disaster management, traffic plan…

cs.CV2026

SpatiaLab: Can Vision-Language Models Perform Spatial Reasoning in the Wild?

Azmine Toushik Wasi, Wahid Faisal, Abdur Rahman +12

Spatial reasoning is a fundamental aspect of human cognition, yet it remains a major challenge for contemporary vision-language models (VLMs). Prior work largely relied on syntheti…