2 citations · 4 across the 4 of their papers we have counts for
4 papers
Multilingual Routing in Mixture-of-Experts
Lucas Bandarkar, Chenyuan Yang, Mohsen Fayyaz +2
Mixture-of-Experts (MoE) architectures have become the key to scaling modern LLMs, yet little is understood about how their sparse routing dynamics respond to multilingual data. In…
Steering MoE LLMs via Expert (De)Activation
Mohsen Fayyaz, Ali Modarressi, Hanieh Deilamsalehy +5
Mixture-of-Experts (MoE) in Large Language Models (LLMs) routes each token through a subset of specialized Feed-Forward Networks (FFN), known as experts. We present SteerMoE, a fra…
Collapse of Dense Retrievers: Short, Early, and Literal Biases Outranking Factual Evidence
Mohsen Fayyaz, Ali Modarressi, Hinrich Schuetze +1
Dense retrieval models are commonly used in Information Retrieval (IR) applications, such as Retrieval-Augmented Generation (RAG). Since they often serve as the first step in these…
Evaluating Human Alignment and Model Faithfulness of LLM Rationale
Mohsen Fayyaz, Fan Yin, Jiao Sun +1
We study how well large language models (LLMs) explain their generations through rationales -- a set of tokens extracted from the input text that reflect the decision-making proces…