Navigating the First Year of the Ukrainian Battlefield: Machine Learning vs. Large Language ModelsMaathuis, C.Kerkhof, I.Journal of Information Warfare
Rethinking machine unlearning for large language models Machine unlearning techniques remove undesirable data and associated model capabilities while preserving essential knowledge, so that machine learning models can be updated without costly retraining. Liu et al. review recent advances and opportunities in...
Thismisguidedtrend has resulted, in our opinion, in an unfortunate state of affairs: an insistence on building NLP systems using ‘large language models’ (LLM) that require massive computing power in a futile attempt at trying toapproximatethe infinite object we call natural language by trying to...
虽然机器翻译(MT)在领域适应性方面已经取得了显著进展,但实时适应仍然是一个巨大的挑战。 研究目标: 本研究的主要目标是探索大规模语言模型(LLMs)在实时自适应MT中的应用,特别是如何利用上下文学习(in-context learning)来改进实时MT的适应性。在上下文学习中,LLM可以通过输入一系列翻译对作为提示,在推理时模拟特定领...
A knowledge gap persists between machine learning (ML) developers (e.g., data scientists) and practitioners (e.g., clinicians), hampering the full utilization of ML for clinical data analysis. We investigated the potential of the ChatGPT Advanced Data An
Large language models are becoming more prominent, enabling sophisticated content creation and enhanced human-computer interactions. Computer vision. Evolving computer vision capabilities are expected to have a profound effect on many domains. In healthcare, it plays an increasingly important role in ...
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In the current job market, machine learning engineers should also consider building some expertise with generative AI. For example, knowing how tofine-tuneand deploy a large language model, then manage it in production -- often referred to asLLMOps-- is a valuable skill for engineers ...
Language models are statistical methods predicting the succession of tokens in sequences, using natural text. Large language models (LLMs) are neural network-based language models with hundreds of millions (BERT) to over a trillion parameters (MiCS), and whose size makes single-GPU training...
Prompts marked as “challenging” have been found by the authors to consistently lead to generation of toxic continuation by tested models (GPT-1, GPT-2, GPT-3, CTRL, CTRL-WIKI); (2) Bias in Open-ended Language Generation Dataset (BOLD), which is a large-scale dataset that consist...