activity
20182026
most citedOpen-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models

2 citations · 4 across the 8 of their papers we have counts for

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10 papers · 1 filter

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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-…

cs.CL20251 cited

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…

cs.CL2025

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…

cs.CL2025

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…