11 citations · 37 across the 35 of their papers we have counts for
13 papers · 1 filter
WebOperator: Action-Aware Tree Search for Autonomous Agents in Web Environment
Mahir Labib Dihan, Tanzima Hashem, Mohammed Eunus Ali +1
LLM-based agents often operate in a greedy, step-by-step manner, selecting actions solely based on the current observation without considering long-term consequences or alternative…
MapAgent: A Hierarchical Agent for Geospatial Reasoning with Dynamic Map Tool Integration
Md Hasebul Hasan, Mahir Labib Dihan, Tanzima Hashem +2
Agentic AI has significantly extended the capabilities of large language models (LLMs) by enabling complex reasoning and tool use. However, most existing frameworks are tailored to…
CompassLLM: A Multi-Agent Approach toward Geo-Spatial Reasoning for Popular Path Query
Md. Nazmul Islam Ananto, Shamit Fatin, Mohammed Eunus Ali +1
The popular path query - identifying the most frequented routes between locations from historical trajectory data - has important applications in urban planning, navigation optimiz…
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…
The Art of Saying "Maybe": A Conformal Lens for Uncertainty Benchmarking in VLMs
Asif Azad, Mohammad Sadat Hossain, MD Sadik Hossain Shanto +2
Vision-Language Models (VLMs) have achieved remarkable progress in complex visual understanding across scientific and reasoning tasks. While performance benchmarking has advanced o…
DashboardQA: Benchmarking Multimodal Agents for Question Answering on Interactive Dashboards
Aaryaman Kartha, Ahmed Masry, Mohammed Saidul Islam +8
Dashboards are powerful visualization tools for data-driven decision-making, integrating multiple interactive views that allow users to explore, filter, and navigate data. Unlike s…
Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team
Md Tanzib Hosain, Salman Rahman, Md Kishor Morol +1
Despite impressive progress on complex reasoning, current large language models (LLMs) typically operate in isolation - treating each problem as an independent attempt, without acc…
AI Debate Aids Assessment of Controversial Claims
Salman Rahman, Sheriff Issaka, Ashima Suvarna +11
As AI grows more powerful, it will increasingly shape how we understand the world. But with this influence comes the risk of amplifying misinformation and deepening social divides-…
TechniqueRAG: Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text
Ahmed Lekssays, Utsav Shukla, Husrev Taha Sencar +1
Accurately identifying adversarial techniques in security texts is critical for effective cyber defense. However, existing methods face a fundamental trade-off: they either rely on…
ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering
Ahmed Masry, Mohammed Saidul Islam, Mahir Ahmed +11
Charts are ubiquitous, as people often use them to analyze data, answer questions, and discover critical insights. However, performing complex analytical tasks with charts requires…
X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents
Salman Rahman, Liwei Jiang, James Shiffer +7
Multi-turn interactions with language models (LMs) pose critical safety risks, as harmful intent can be strategically spread across exchanges. Yet, the vast majority of prior work…
CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging
Md. Ashraful Islam, Mohammed Eunus Ali, Md Rizwan Parvez
Large Language Models (LLMs) have made significant strides in code generation and problem solving. Current approaches employ external tool-based iterative debuggers that use compil…
MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
Mahir Labib Dihan, Md Tanvir Hassan, Md Tanvir Parvez +5
Recent advancements in foundation models have improved autonomous tool usage and reasoning, but their capabilities in map-based reasoning remain underexplored. To address this, we…