Large Language Models
Reasoning, agency, safety, and scientific discovery.
Persian Benchmarks
High-quality evaluation resources for reasoning and generation in a low-resource language.
Reasoning
Methods for more systematic, compositional, and logically consistent multi-step reasoning.
LLM Agents
Planning, memory, tool use, and coordination in long-horizon environments.
Scientific Discovery
Language models as tools for idea generation, pattern discovery, and scientific reasoning.
Chain-of-Thought Faithfulness
Evaluation of deceptive or misleading reasoning behavior in language models.
Publications
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TMLR 2026
Large Language Models for Scientific Idea Generation: A Creativity-Centered Survey
Fatemeh Shahhosseini, Arash Marioriyad, Ali Momen, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban, Shaghayegh Haghjooy Javanmard
Surveys the use of large language models for scientific idea generation through a creativity-centered framework and evaluation perspective.
Transactions on Machine Learning Research (TMLR), 2026
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arXiv 2026
Lying to Win: Assessing LLM Deception through Human-AI Games and Parallel-World Probing
Arash Marioriyad, Alireza Nouri, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah
Evaluates strategic deception through interactive games and probes whether models represent truthful and deceptive alternatives internally.
arXiv preprint, 2026
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arXiv 2026
The Judge Who Never Admits: Hidden Shortcuts in LLM-Based Evaluation
Arash Marioriyad, Omid Ghahroodi, Ehsan Asgari, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah
Shows that language-model judges can exploit hidden shortcuts while producing explanations that fail to acknowledge those cues.
arXiv preprint, 2026
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ACL 2025
CER: Confidence Enhanced Reasoning in LLMs
Ali Razghandi, Seyed Mohammad Hadi Hosseini, Mahdieh Soleymani Baghshah
Uses model confidence to improve reasoning reliability and help language models make better decisions during multi-step inference.
Annual Meeting of the Association for Computational Linguistics (ACL), 2025
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arXiv 2025
The Illusion of Procedural Reasoning: Measuring Long-Horizon FSM Execution in LLMs
Mohammad Mahdi Samiei, Mohammad Mansouri, Mahdieh Soleymani Baghshah
Tests long-horizon finite-state-machine execution to separate genuine procedural reasoning from shallow pattern matching.
arXiv preprint, 2025
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arXiv 2025
Unspoken Hints: Accuracy Without Acknowledgement in LLM Reasoning
Arash Marioriyad, Soroush Adim, Nima Alighardashi, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban
Examines cases where implicit hints improve answers even though model explanations do not acknowledge using them.
arXiv preprint, 2025
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arXiv 2025
The Silent Judge: Unacknowledged Shortcut Bias in LLM-as-a-Judge
Arash Marioriyad, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah
Demonstrates that LLM evaluators can rely on shortcut signals while presenting apparently independent justifications for their scores.
arXiv preprint, 2025