5 papers
AF-Muon: An AdamW-Free Muon Optimizer for Tied-Embedding Models
Arash Lagzian, Paniz Halvachi, Junming Zhang +2
Muon improves large-scale training by applying a spectral-norm steepest-descent update to matrix parameters, but practical models also contain parameter blocks that do not fit dens…
MIRAGE: Multi-Perspective Creative Language Model Reasoning with Reinforcement Learning Guidance
Arash Lagzian, Srinivas Anumasa, Dianbo Liu
Recent advances in Large Language Models (LLMs) have revolutionized artificial intelligence and how human interact with AIs. Despite impressive advancements, LLMs struggle with com…
Human-like Content Analysis for Generative AI with Language-Grounded Sparse Encoders
Yiming Tang, Arash Lagzian, Srinivas Anumasa +9
The rapid development of generative AI has transformed content creation, communication, and human development. However, this technology raises profound concerns in high-stakes doma…
Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming
Arash Lagzian, Srinivas Anumasa, Dianbo Liu
Large Language Models (LLMs) demonstrate remarkable proficiency in generating accurate and fluent text. However, they often struggle with diversity and novelty, leading to repetiti…
KhabarChin: Automatic Detection of Important News in the Persian Language
Hamed Hematian Hemati, Arash Lagzian, Moein Salimi Sartakhti +2
Being aware of important news is crucial for staying informed and making well-informed decisions efficiently. Natural Language Processing (NLP) approaches can significantly automat…