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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Topbots

JUNE 15, 2023

Discussion Implications of tokenization language disparity Overall, requiring more tokens (to tokenize the same message in a different language) means: You’re limited by how much information you can put in the prompt (because the context window is fixed). Indo-European, Sino-Tibetan).[

Natural Language Processing 59

Natural Language Processing Computational Linguistics NLP ChatGPT 59

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. Prompts are changed by introducing spelling errors, replacing synonyms, concatenating irrelevant information or translating from a different language.

Machine Learning 80

Machine Learning NLP Large Language Models LLM 80

Google Research AI blog

JULY 10, 2023

Posted by Malaya Jules, Program Manager, Google This week, the 61st annual meeting of the Association for Computational Linguistics (ACL), a premier conference covering a broad spectrum of research areas that are concerned with computational approaches to natural language, is taking place online.

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Large Language Models Natural Language Processing NLP Computational Linguistics 93

Marktechpost

AUGUST 15, 2024

Metaphor Components Identification (MCI) is an essential aspect of natural language processing (NLP) that involves identifying and interpreting metaphorical elements such as tenor, vehicle, and ground. The primary issue in MCI lies in the complexity and diversity of metaphors.

NLP 60

NLP Large Language Models Computational Linguistics Neural Network 60

NLP People

JUNE 5, 2018

For more information check their jobs section. Utilising natural language understanding, they provide solutions that literally ‘speak human language’ by making users free from the need to acquire technical jargon. From time to time the company hires NLP-related specialists for their office in Berlin. They are hiring.

NLP 52

NLP Data Mining Deep Learning Machine Learning 52

Topbots

JANUARY 30, 2023

Since the wind is coming from Maria’s direction, she asks “Maria” for a report on current weather conditions as an important piece of information. Another important limitation, as of now, is the recency of the information. When we use language, we do so for a specific purpose, which is our communicative intent.

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Large Language Models Computational Linguistics LLM Natural Language Processing 52

NLP People

JANUARY 2, 2019

Hundreds of researchers, students, recruiters, and business professionals came to Brussels this November to learn about recent advances, and share their own findings, in computational linguistics and Natural Language Processing (NLP).

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BERT Natural Language Processing Computational Linguistics NLP 52

AWS Machine Learning Blog

MAY 22, 2023

Solution overview The target task in this post is to, given a chunk of text in the prompt, return questions that are related to the text but can’t be answered based on the information it contains. This is a useful task to identify missing information in a description or identify whether a query needs more information to be answered.

Machine Learning 106

Machine Learning Natural Language Processing Computational Linguistics NLP 106

Sebastian Ruder

AUGUST 18, 2019

Different architectures show different layer-wise trends in terms of what information they capture ( Liu et al., The general setup in probing tasks used to study linguistic knowledge within contextual word representations ( Liu et al., On the whole, it is difficult to learn certain types of information from raw text.

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NLP BERT Natural Language Processing Computational Linguistics 75

Heartbeat

FEBRUARY 21, 2023

Picture by Anna Nekrashevich , Pexels.com Introduction Sentiment analysis is a natural language processing technique which identifies and extracts subjective information from source materials using computational linguistics and text analysis.

NLP 52

NLP Natural Language Processing Machine Learning Computational Linguistics 52

Viso.ai

JULY 18, 2024

LLMs changed how we interact with the internet as finding relevant information or performing specific tasks was never this easy before. What are Large Language Models (LLMs)? In generative AI, human language is perceived as a difficult data type.

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Large Language Models Neural Network Natural Language Processing BERT 52

Sebastian Ruder

NOVEMBER 14, 2022

Developing models that work for more languages is important in order to offset the existing language divide and to ensure that speakers of non-English languages are not left behind, among many other reasons. On the one hand, data should reflect the background of the speakers speaking the language.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Bugra Akyildiz

JULY 16, 2023

Google created a new learning path guides you through a curated collection of content on generative AI products and technologies, from the fundamentals of Large Language Models to how to create and deploy generative AI solutions on Google Cloud.

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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. Using a tool like neptune.ai

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BERT Natural Language Processing ML Deep Learning 52

The Stanford AI Lab Blog

FEBRUARY 1, 2022

Informed by prior work, we test the following 4 hypotheses: Redirect - Inspired by Brahnam 5 , we hypothesize that using explicit redirection when responding to an offensive user utterance is an effective strategy. Ideally, everyone would take turns responding to prompts, sharing information about themselves, and introducing new topics.

Computational Linguistics 40

Computational Linguistics Chatbots Robotics Natural Language Processing 40

NLP People

SEPTEMBER 12, 2017

This job brought me in close contact with a large number of IT researchers, and some of them happened to work in computational linguistics and machine learning. This was when I realized I might try to pursue this path too, as it would allow me to combine my passion for languages and interest in technologies.

Computational Linguistics 52

Computational Linguistics Machine Learning Data Mining Natural Language Processing 52

John Snow Labs

DECEMBER 26, 2023

In today’s enormous digital environment, where information flows at breakneck speed, determining the sentiment concealed inside textual data has become critical. On the other hand, Sentiment analysis is a method for automatically identifying, extracting, and categorizing subjective information from textual data. Daly, Peter T.

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Neural Network Computational Linguistics NLP Machine Learning 52

Mlearning.ai

FEBRUARY 6, 2023

From uncovering patterns of human behavior to predicting the spread of ideas and information, the application of graph theory in social network analysis holds immense promise. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [7] Attention is not Explanation. Weigreffe, Y.

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Explainable AI Explainability ChatGPT Chatbots 52

AWS Machine Learning Blog

MARCH 2, 2023

Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to help separate out the relevant and meaningful facts and figures. She has a technical background in AI and Natural Language Processing.

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BERT Deep Learning Metadata Auto-complete 88

Sebastian Ruder

FEBRUARY 23, 2023

 Instead of learning module parameters directly, they can be generated using an auxiliary model (a hypernetwork) conditioned on additional information and metadata. We provide a high-level overview of some of the trade-offs of the different computation functions below. Speech processing. Module parameter generation.  Instead

Deep Learning 52

Deep Learning NLP Computer Vision Metadata 52

Ines Montani

MAY 9, 2017

In this post I’ll share some lessons we’ve learned from running spaCy , the popular and fast-growing library for Natural Language Processing in Python. Challenges for open-source NLP One of the biggest challenges for Natural Language Processing is dealing with fast-moving and unpredictable technologies.

NLP 52

NLP Natural Language Processing Computational Linguistics Deep Learning 52

Explosion

DECEMBER 28, 2019

Ines’ talk in the language track, “Practical Transfer Learning for NLP with spaCy and Prodigy” , focused on the increasing trend of initializing models with information from large raw-text corpora, and how you can use this type of technique in spaCy and Prodigy. Sep 4: spacy-transformers kept getting better as we released v0.4.0,

NLP 52

NLP BERT Machine Learning Python 52

Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). Alternatively, FNet [27] uses 1D Fourier Transforms instead of self-attention to mix information at the token level.   2021 saw several breakthroughs in ML applied to advance the natural sciences.

NLP 52

NLP ML BERT Computational Linguistics 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. What happened?

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Neural Network Data Science AI AI 52

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. We make practical recommendations such as documenting dialect, style, and register information in datasets.

NLP 52

NLP Natural Language Processing Computational Linguistics Neural Network 52

Sebastian Ruder

DECEMBER 6, 2021

Information retrieval (IR) methods are used to retrieve the relevant paragraphs. In addition, for many domains, the structure of the unlabelled data can contain information that may be useful for the end task. For such languages, datasets must necessarily be cross-lingual. Classic sparse methods such as BM25 ( Robertson et al.,

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52

Snorkel AI

JUNE 14, 2023

What information do you want to include? Let’s double-click into correctness to describe our approach on how technology, and specifically machine learning and natural language processing, can come together in a very user-centric way to solve real problems that our users face every single day.

Machine Learning 52

Machine Learning Natural Language Processing Data Scientist Computational Linguistics 52

Snorkel AI

JUNE 14, 2023

What information do you want to include? Let’s double-click into correctness to describe our approach on how technology, and specifically machine learning and natural language processing, can come together in a very user-centric way to solve real problems that our users face every single day.

Machine Learning 52

Machine Learning Natural Language Processing Data Scientist Computational Linguistics 52

Explosion

MAY 8, 2016

Moreover, unlike some cases where you could change your linguistic theory to avoid the crossing arcs, this one is well motivated by data and very difficult to avoid without losing information. To summarize the above, we need non-projective trees to represent the information that we are interested in when parsing natural language.

Convolutional Neural Networks 40

Convolutional Neural Networks NLP Algorithm Neural Network 40

Probably Approximately a Scientific Blog

JULY 13, 2015

After I dedicated the previous post to the awesome field of natural language processing, in this post I will drill down and tell you about the specific task that I'm working on: recognizing lexical inference. Proceedings of the 14th conference on Computational linguistics-Volume 2. ↩ [3] Harris, Zellig S.

Computational Linguistics 52

Computational Linguistics Natural Language Processing NLP 52

AWS Machine Learning Blog

AUGUST 8, 2024

By integrating LLMs, the WxAI team enables advanced capabilities such as intelligent virtual assistants, natural language processing (NLP), and sentiment analysis, allowing Webex Contact Center to provide more personalized and efficient customer support.

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AWS Machine Learning Blog

AUGUST 8, 2024

By integrating LLMs, WxAI team enables advanced capabilities such as intelligent virtual assistants, natural language processing, and sentiment analysis, allowing Webex Contact Center to provide more personalized and efficient customer support.

Software Engineer 114

Software Engineer Large Language Models Generative AI Computational Linguistics 114

NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Hirst (2017).

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. Given enough context (e.g. This can either be by searching for a pattern (e.g.

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Natural Language Processing NLP Machine Learning Computational Linguistics 52