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simplilearn.com /2 weeks ago

Natural Language Processing Techniques: A Beginner’s Guide | Simplilearn

TL;DR: NLP helps computers understand, read, analyze, and generate human language. Common NLP techniques include tokenization, stemming, lemmatization, POS tagging, named entity re...

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bioengineer.org /1 week ago

NLP Outperforms ICD-10 in Capturing Clinical Data

In a groundbreaking development poised to transform clinical data interpretation, recent research has demonstrated that Natural Language Processing (NLP) tools vastly outperform th...

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elearningindustry.com /1 month ago

From "Where's The Report?" To "Here's The Answer": How AI Is Finally Speaking L&D's Language

NLQ, NLU, and NLG explained for L&D professionals—what each technology actually does, and how together they replace static reports with real-time answers that business leaders...

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medinform.jmir.org /5 days ago

Natural Language Processing Applied to Psychiatric Clinical Notes: Scoping Review

Background: Psychiatric clinical notes in electronic health records (EHRs) provide rich longitudinal information that can support clinical decision-making. Using historical medical...

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neurosciencenews.com /1 week ago

LLMs and Math Combine to Map Human Decision-Making

A new research framework that combines large language models (LLMs) with choice mathematics to evaluate human decision-making. By deploying LLMs to automatically interpret and code...

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dzone.com /1 month ago

LLM-Powered Deep Parsing for Industrial Inventory Search

Industrial ERPs often look structured on the surface: item IDs, purchase orders, stock levels. But in many companies, they are overloaded with unintentional duplicates because the...

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habr.com /1 week ago

Топ вопросов с NLP собеседований: обучение LLM, prompt-engineering и alignment

На NLP/LLM собеседованиях часто проверяют не только знание архитектуры Transformer, но и понимание полного жизненного цикла современной LLM: как модель предобучается, почему обычна...

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neurosciencenews.com /3 weeks ago

Human Brains and AI Share Predictive Language Processing Principles

The human brain and Large Language Models (LLMs) organize and predict language using deeply parallel information processing principles.

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medium.com /1 month ago

機器學習：自然語言處理 (NLP) — 2

讀者筆記：這是我在學習 NVIDIA: Building Transformer-Based NLP Applications 過程中的記錄。內容若有理解偏差或技術錯誤，懇請各位前輩不吝在評論區指正，讓我們一起交流進步！Continue rea...

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simplilearn.com /5 days ago

SLM vs LLM: Key Differences and Use Cases | Simplilearn

TL;DR: LLMs and SLMs are two types of language models used in artificial intelligence systems. LLMs are built to handle large-scale tasks with higher reasoning ability, while SLMs...

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neurosciencenews.com /1 month ago

Stroop Test Exposes Inherent LLM Flaw

Can an advanced artificial intelligence truly exercise decision-making control, or is it merely trapped in an inescapable loop of automatic pattern mimicry? A cognitive science stu...

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r-bloggers.com /2 weeks ago

Running local LLMs on your NPU from R with Foundry Local and ellmer

TLDR: this post summarizes how I was able to leverage my Surface Pro 11’s Neural Processing Unit (NPU) to chat […] The post Running local LLMs on your NPU from R with Foundry Local...

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kdnuggets.com /3 weeks ago

3 NLTK Tricks for Advanced Text Preprocessing & Linguistic Analysis

In this article, we will walk through three essential NLTK tricks to elevate your text preprocessing: preserving phrase integrity with the MWETokenizer, context-aware lemmatization...

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kdnuggets.com /3 weeks ago

3 NLTK Tricks for Advanced Text Preprocessing & Linguistic Analysis

In this article, we will walk through three essential NLTK tricks to elevate your text preprocessing: preserving phrase integrity with the MWETokenizer, context-aware lemmatization...

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techblog.lycorp.co.jp /3 weeks ago

プロンプトは人手チューニングからAIチューニングへ：遺伝的アルゴリズムで回す自動最適化と高速化

LINEヤフーの技術カンファレンス「Tech-Verse 2026」の公式記事です。こんにちは。LINEヤフー株式会社の中野です。Yahoo!検索のAI回答サービスで大規模言語モデル（LLM）の最適化...

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towardsdatascience.com /3 weeks ago

Structured Outputs with LLMs: JSON Mode, Function Calling, and When to Use Each

Getting reliable, readable responses out of your LLM, and knowing which tool to reach for The post Structured Outputs with LLMs: JSON Mode, Function Calling, and When to Use Each a...

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artificialintelligence-news.com /2 weeks ago

Advances in Natural Language Processing Are Changing Professional Networking

Natural language processing is reshaping professional communication on online platforms, enabling more relevant and personalised networking interactions. As AI-driven systems incre...

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nextweekai.com /3 weeks ago

How to Build ChatGPT From Scratch (with JavaScript): Understanding LLMs Step by Step

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habr.com /1 month ago

Ненормальное марковское программирование

Какие программы могут быть по-настоящему достойны хаба "ненормальное программирование"?Конечно же, программы для нормальных марковских алгорифмов! (Далее - НАМ).Но, будем честны пе...

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marktechpost.com /1 month ago

Nous Research Releases Contrastive Neuron Attribution (CNA): Sparse MLP Circuit Steering Without SAE Training or Weight...

Nous Research releases Contrastive Neuron Attribution (CNA), a method that identifies and ablates sparse MLP neuron circuits to steer LLM behavior — no sparse autoencoder training,...

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kdnuggets.com /1 month ago

Practical NLP in the Browser with Transformers.js

This tutorial covers three NLP tasks: text classification, zero-shot labelling, and question answering using Transformers.js's pipeline() API.

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kdnuggets.com /1 month ago

5 Fun Papers That Explain LLMs Clearly

Want to understand LLMs better? Start with these five foundational papers that explain how they work.

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kdnuggets.com /1 month ago

5 Fun Papers That Explain LLMs Clearly

Want to understand LLMs better? Start with these five foundational papers that explain how they work.

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towardsdatascience.com /2 weeks ago

An LLM as arbiter in RAG retrieval: picking the right candidate with reasons

Enterprise Document Intelligence [Vol.1 #7C] - One LLM call ranks the candidates with reasons. The output is one typed object your auditor can defend The post An LLM as arbiter in...

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