activity
20232026
most citedDynamic Co-Optimization Compiler: Leveraging Multi-Agent Reinforcement Learning for Enhanced DNN Accelerator Performance

2 citations · 4 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Fair on the Surface? Benchmarking Hidden-Output Fairness Gaps in LLM Recommenders

Chan Aristella Lu, Arya Fayyazi, Junhao Zhang +6

Fairness audits for LLM-based recommenders have largely focused on observable outputs, implicitly assuming that stable recommendations reflect stable internal processing. We challe…

cs.CL2026

COFT: Counterfactual-Conformal Decoding for Fair Chain-of-Thought Reasoning in Large Language Models

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

Large language models (LLMs) can reveal and amplify societal biases during chain-of-thought (CoT) generation. We present COFT (Chain of Fair Thought), a training-free decoding meth…

cs.CV2026

Proof-of-Perception: Certified Tool-Using Multimodal Reasoning with Compositional Conformal Guarantees

Arya Fayyazi, Haleh Akrami

We present Proof-of-Perception (PoP), a tool-using framework that casts multimodal reasoning as an executable graph with explicit reliability guarantees. Each perception or logic n…

cs.LG2025

MARCO: Hardware-Aware Neural Architecture Search for Edge Devices with Multi-Agent Reinforcement Learning and Conformal Prediction Filtering

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

This paper introduces MARCO (Multi-Agent Reinforcement learning with Conformal Optimization), a novel hardware-aware framework for efficient neural architecture search (NAS) target…

cs.CV2025

FAIR-SIGHT: Fairness Assurance in Image Recognition via Simultaneous Conformal Thresholding and Dynamic Output Repair

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

We introduce FAIR-SIGHT, an innovative post-hoc framework designed to ensure fairness in computer vision systems by combining conformal prediction with a dynamic output repair mech…

cs.IR2025★ 2 cited

FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

We propose FACTER, a fairness-aware framework for LLM-based recommendation systems that integrates conformal prediction with dynamic prompt engineering. By introducing an adaptive…