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Mobile Intelligence Language Understanding Benchmark
This technical report introduces Mobile-MMLU, a new benchmark designed to evaluate large language models (LLMs) specifically for mobile devices, addr…
1Â year, 2Â months ago
AI-RAN: Converging Communications and Computing
This document presents AI-RAN, a paradigm shift integrating Radio Access Network (RAN) and Artificial Intelligence (AI) workloads onto a unified plat…
1Â year, 2Â months ago
Ollama LLM Fine-Tuning Methods
These sources collectively explain that fine-tuning is a process of retraining a pre-trained Large Language Model on a specialized dataset to enhance…
1Â year, 2Â months ago
Customizing LLMs for High-Performance VHDL Design
This document describes the development of a Large Language Model (LLM) specifically tailored for explaining VHDL code within a high-performance proc…
1Â year, 2Â months ago
Adaptively Weighted Nearest Neighbors for Matrix Completion
This document introduces and analyzes AWNN (Adaptively Weighted Nearest Neighbors), a novel matrix completion method. Traditional Nearest Neighbor (N…
1Â year, 2Â months ago
SAD Neural Networks, Divergent Gradient Flows, and Optimality
This academic paper explores the training dynamics of neural networks, specifically focusing on gradient flow for fully connected feedforward network…
1Â year, 2Â months ago
WavReward: Evaluating Spoken Dialogue Models
This academic paper introduces WavReward, a novel evaluation system for end-to-end spoken dialogue models, which process speech input and output dire…
1Â year, 2Â months ago
BLIP3-o Unified Multimodal Models
This academic paper introduces BLIP3-o, a suite of cutting-edge multimodal models designed for both understanding and generating images. The research…
1Â year, 2Â months ago
CodePDE: LLM-Driven PDE Solver Generation
This document introduces CodePDE, a new framework for using large language models (LLMs) to generate code that solves partial differential equations …
1Â year, 2Â months ago
Online Learning Neural Networks: Bounds and Characterization
This research investigates online learning for feedforward neural networks utilizing the sign activation function. The paper identifies a margin cond…
1Â year, 2Â months ago