AssemblyAI

SEPTEMBER 18, 2023

However, among all the modern-day AI innovations, one breakthrough has the potential to make the most impact: large language models (LLMs). These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications.

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Large Language Models BERT Auto-complete LLM 130

John Snow Labs

DECEMBER 26, 2023

Sentiment analysis, a branch of natural language processing (NLP), has evolved as an effective method for determining the underlying attitudes, emotions, and views represented in textual information. Sentiment Analysis Using Simplified Long Short-term Memory Recurrent Neural Networks. abs/2005.03993 Andrew L.

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Neural Network Computational Linguistics NLP Natural Language Processing 52

NLP People

JUNE 5, 2018

DeepL DeepL is a Cologne-based startup that utilises deep neural networks to build state-of-the-art machine translation service. spaCy spaCy is an open-source software library for advanced industrial-strength NLP, created by Explosion AI, a digital studio specialising in Artificial Intelligence and Natural Language Processing.

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NLP Data Mining Deep Learning Natural Language Processing 52

Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. As humans we do not know exactly how we learn language: it just happens.

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Neural Network AI AI Data Science 52

The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing.

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BERT Natural Language Processing ML Deep Learning 52

Sebastian Ruder

FEBRUARY 23, 2023

Computation Function We consider a neural network $f_theta$ as a composition of functions $f_{theta_1} odot f_{theta_2} odot ldots odot f_{theta_l}$, each with their own set of parameters $theta_i$. d) Hypernetwork: A small separate neural network generates modular parameters conditioned on metadata.

Deep Learning 52

Deep Learning NLP Computer Vision Metadata 52

Sebastian Ruder

AUGUST 18, 2019

This goes back to layer-wise training of early deep neural networks ( Hinton et al., Instead, we train layers individually to give them time to adapt to the new task and data. 2006 ; Bengio et al., Recent approaches ( Felbo et al., 2017 ; Howard and Ruder, 2018 ; Chronopoulou et al.,

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NLP BERT Natural Language Processing Computational Linguistics 75

Marek Rei

NOVEMBER 4, 2024

I have written short summaries of 68 different research papers published in the areas of Machine Learning and Natural Language Processing. Computational Linguistics 2022. link] Developing a system for the detection of cognitive impairment based on linguistic features. University of Szeged.

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Machine Learning NLP Large Language Models LLM 80

Sebastian Ruder

JUNE 6, 2022

The initiative focuses on making Computational Linguistics (CL) research accessible in 60 languages and across all modalities, including text/speech/sign language translation, closed captioning, and dubbing. Extracted structures can be further generalized into patterns and event schemas.

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NLP Natural Language Processing Computational Linguistics Neural Network 52

Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). Transactions of the Association for Computational Linguistics, 9, 978–994. Transactions of the Association for Computational Linguistics, 9, 570–585. Schneider, R., Alayrac, J.

NLP 52

NLP ML BERT Computational Linguistics 52

Explosion

MAY 8, 2016

We’ve since released spaCy v2.0 , which comes with new convolutional neural network models for German and other languages. In the same way that a physicist might assume a frictionless surface or a spherical cow , sometimes it’s useful for computational linguists to assume projective trees and context-free grammars.

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Convolutional Neural Networks NLP Neural Network Algorithm 40

Explosion

DECEMBER 17, 2013

Natural languages introduce many unexpected ambiguities, which our world-knowledge immediately filters out. It would be relatively easy to provide a beam-search version of spaCy…But, I think the gap in accuracy will continue to close, especially given advances in neural network learning.

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Python Algorithm NLP Computational Linguistics 45

Mlearning.ai

FEBRUARY 6, 2023

The classifier currently only works on English text, but not on other languages or on code [3]. Classifiers based on neural networks are known to be poorly calibrated outside of their training data [3]. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [7]

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Explainable AI Explainability ChatGPT Chatbots 52

ODSC - Open Data Science

MARCH 6, 2024

Artificial Intelligence has made significant strides since its inception, evolving from simple algorithms to highly advanced Neural Networks capable of performing sophisticated tasks such as generating completely new content, including images, audio, and video. She is currently part of the Artificial Intelligence Practice at Avanade.

Responsible AI 52

Responsible AI Generative AI Natural Language Processing Artificial Intelligence 52

NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. Neural Networks are the workhorse of Deep Learning (cf. Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]. Toutanova (2018). Goldberg and G.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

Probably Approximately a Scientific Blog

OCTOBER 30, 2017

For example, this blog post is published in a blog that largely discusses natural language processing, so if I write "NLP", you'd know I refer to natural language processing rather than to neuro-linguistic programming. Today, similarly to other NLP tasks, parsers are mostly based on neural networks.

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Natural Language Processing NLP Machine Learning Computational Linguistics 52