18 papers
A Jagged Frontier: Evaluating Robustness of Code Agents to Semantics-Preserving Transformations
Hasan Najib Mahmud, Shreya Gupta, Isha Chaudhary +4
AI code agents are increasingly deployed to resolve real software issues, yet their reliability under superficial code variations remains poorly understood. We evaluate whether cod…
Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery
Syed Rifat Raiyan, Mohsinul Kabir, Hasan Mahmud +2
Mathematical reasoning has long served as a stringent test of machine intelligence; over the past decade, it has moved from a niche problem within NLP to one of the most consequent…
LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution
Adib Sakhawat, Syed Rifat Raiyan, Tahsin Islam +3
We argue, with systematic empirical evidence, that a large language model's political ideology is not a fixed point, but a conditional distribution positionconte…
Coordinates of Capability: A Unified MTMM-Geometric Framework for LLM Evaluation
Adib Sakhawat, Tahsin Islam, Takia Farhin +3
The evaluation of Large Language Models (LLMs) faces a critical challenge in construct validity, where fragmented benchmarks and ad hoc metrics frequently conflate method variance,…
Courtroom-Style Multi-Agent Debate with Progressive RAG and Role-Switching for Controversial Claim Verification
Masnun Nuha Chowdhury, Nusrat Jahan Beg, Umme Hunny Khan +3
Large language models (LLMs) remain unreliable for high-stakes claim verification due to hallucinations and shallow reasoning. While retrieval-augmented generation (RAG) and multi-…
Beyond Symbolic Solving: Multi Chain-of-Thought Voting for Geometric Reasoning in Large Language Models
Md. Abu Bakor Siddique, Shahrin Hossain, Sadman Ahmed Siam +3
Geometric Problem Solving (GPS) remains at the heart of enhancing mathematical reasoning in large language models because it requires the combination of diagrammatic understanding,…