1 citations · 1 across the 8 of their papers we have counts for
8 papers
Same Game, Different Story: A Minimal Conservative Strategic Robustness Benchmark for Large Language Model Agents
Seyed Pouyan Mousavi Davoudi, Arshia Gharagozlou, Alireza Amiri-Margavi +2
Large language model agents are increasingly deployed in settings where the value of an action depends on what other agents do. This creates a strategic reliability problem: the sa…
Do Large Language Model Voters Strategize? An Oracle-Based Benchmark for Manipulation under Voting Rules
Seyed Pouyan Mousavi Davoudi, Arshia Gharagozlou, Alireza Amiri-Margavi +2
Strategic voting is a canonical failure mode for collective choice: a voter may obtain a more preferred outcome by reporting a ballot that differs from its true preferences. This p…
Truthful AI Advisors: A Pre-Specified Benchmark for Large Language Model Honesty Under Preference Misalignment
Hamidreza Hasani Balyani, Seyed Pouyan Mousavi Davoudi, Alireza Amiri-Margavi +2
Large language models are increasingly deployed as advisors whose objective is not aligned with the user's: recommenders optimize for engagement, sales assistants for purchases. Wh…
Equal Access, Unequal Interaction: A Counterfactual Audit of LLM Fairness
Alireza Amiri-Margavi, Arshia Gharagozlou, Amin Gholami Davodi +2
Prior work on fairness in large language models (LLMs) has primarily focused on access-level behaviors such as refusals and safety filtering. However, equitable access does not ens…
Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models
Arash Gholami Davoodi, Navid Rezazadeh, Seyed Pouyan Mousavi Davoudi +1
Large language models (LLMs) must balance diversity and creativity against logical coherence in open-ended generation. Existing truncation-based samplers are effective but largely…
Collective Reasoning Among LLMs: A Framework for Answer Validation Without Ground Truth
Seyed Pouyan Mousavi Davoudi, Amin Gholami Davodi, Alireza Amiri-Margavi +2
We introduce a new approach in which several advanced large language models-specifically GPT-4-0125-preview, Meta-LLAMA-3-70B-Instruct, Claude-3-Opus, and Gemini-1.5-Flash-collabor…
Enhancing Answer Reliability Through Inter-Model Consensus of Large Language Models
Alireza Amiri-Margavi, Iman Jebellat, Ehsan Jebellat +1
We propose a collaborative framework in which multiple large language models -- including GPT-4-0125-preview, Meta-LLaMA-3-70B-Instruct, Claude-3-Opus, and Gemini-1.5-Flash -- gene…
LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs
Arash Gholami Davoodi, Seyed Pouyan Mousavi Davoudi, Pouya Pezeshkpour
Large language models (LLMs) demonstrate impressive capabilities in mathematical reasoning. However, despite these achievements, current evaluations are mostly limited to specific…