4 papers
Sink-Aware Pruning for Diffusion Language Models
Aidar Myrzakhan, Tianyi Li, Bowei Guo +2
Diffusion Language Models (DLMs) incur high inference cost due to iterative denoising, motivating efficient pruning. Existing pruning heuristics largely inherited from autoregressi…
DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
Jennifer Chen, Aidar Myrzakhan, Yaxin Luo +3
Retrieval-Augmented Generation (RAG) methods have proven highly effective for tasks requiring factual consistency and robust knowledge retrieval. However, large-scale RAG systems c…
Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark
Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan +6
Rapid advancements in large language models (LLMs) have increased interest in deploying them on mobile devices for on-device AI applications. Mobile users interact differently with…
Open-LLM-Leaderboard: From Multi-choice to Open-style Questions for LLMs Evaluation, Benchmark, and Arena
Aidar Myrzakhan, Sondos Mahmoud Bsharat, Zhiqiang Shen
Multiple-choice questions (MCQ) are frequently used to assess large language models (LLMs). Typically, an LLM is given a question and selects the answer deemed most probable after…