UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
Z80-μLM is a 'conversational AI' that generates short character-by-character sequences, with quantization-aware training (QAT) to run on a Z80 processor with 64kb of ram. The root behind this project ...
Abstract: Programming language source code vulnerability mining is crucial to improving the security of software systems, but current research is mostly focused on the C language field, with little ...
Moreover, we discuss strategies for metadata selection and human evaluation to ensure the quality and effectiveness of ITDs. By integrating these elements, this tutorial provides a structured ...
Abstract: The advancement in technology has improved the accessibility of communications for a person with hearing impairment significantly. A full implementation approach for sign language ...
In this tutorial, we implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We combine TRL’s DPOTrainer ...
In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...
GitHub's 2025 Octoverse reveals TypeScript added 1M+ contributors to claim #1 spot, as typed languages become essential for AI-assisted development workflows. TypeScript has dethroned Python as the ...
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