11 citations · 20 across the 40 of their papers we have counts for
9 papers · 1 filter
Lying to Win: Assessing LLM Deception through Human-AI Games and Parallel-World Probing
Arash Marioriyad, Ali Nouri, Mohammad Hossein Rohban +1
As Large Language Models (LLMs) transition into autonomous agentic roles, the risk of deception-defined behaviorally as the systematic provision of false information to satisfy ext…
The Judge Who Never Admits: Hidden Shortcuts in LLM-based Evaluation
Arash Marioriyad, Omid Ghahroodi, Ehsaneddin Asgari +2
Large language models (LLMs) are increasingly used as automatic judges to evaluate system outputs in tasks such as reasoning, question answering, and creative writing. A faithful j…
Mechanistic Interpretability of Large-Scale Counting in LLMs through a System-2 Strategy
Hosein Hasani, Mohammadali Banayeeanzade, Ali Nafisi +5
Large language models (LLMs), despite strong performance on complex mathematical problems, exhibit systematic limitations in counting tasks. This issue arises from the architectura…
Large Language Models for Scientific Idea Generation: A Creativity-Centered Survey
Fatemeh Shahhosseini, Arash Marioriyad, Ali Momen +3
Scientific idea generation is central to discovery, requiring the joint satisfaction of novelty and scientific soundness. Unlike standard reasoning or general creative generation,…
The Silent Judge: Unacknowledged Shortcut Bias in LLM-as-a-Judge
Arash Marioriyad, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah
Large language models (LLMs) are increasingly deployed as automatic judges to evaluate system outputs in tasks such as summarization, dialogue, and creative writing. A faithful jud…
Unspoken Hints: Accuracy Without Acknowledgement in LLM Reasoning
Arash Marioriyad, Shaygan Adim, Nima Alighardashi +2
Large language models (LLMs) increasingly rely on chain-of-thought (CoT) prompting to solve mathematical and logical reasoning tasks. Yet, a central question remains: to what exten…