3 papers
cs.MA2025
An Adversary-Resistant Multi-Agent LLM System via Credibility Scoring
Sana Ebrahimi, Mohsen Dehghankar, Abolfazl Asudeh
While multi-agent LLM systems show strong capabilities in various domains, they are highly vulnerable to adversarial and low-performing agents. To resolve this issue, in this paper…
cs.LG2024
[Experiments & Analysis] Evaluating the Feasibility of Sampling-Based Techniques for Training Multilayer Perceptrons
Sana Ebrahimi, Rishi Advani, Abolfazl Asudeh
The training process of neural networks is known to be time-consuming, and having a deep architecture only aggravates the issue. This process consists mostly of matrix operations,…
cs.CL2024
REQUAL-LM: Reliability and Equity through Aggregation in Large Language Models
Sana Ebrahimi, Nima Shahbazi, Abolfazl Asudeh
The extensive scope of large language models (LLMs) across various domains underscores the critical importance of responsibility in their application, beyond natural language proce…