ODSC - Open Data Science

APRIL 3, 2023

QA is a critical area of research in NLP, with numerous applications such as virtual assistants, chatbots, customer support, and educational platforms. Another research line in SQuARE is how to make information retrieval more effective. One type of user question is information-seeking. Euro) in 2021. Sung-Hyon Myaeng.

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Sebastian Ruder

AUGUST 18, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP. In the span of little more than a year, transfer learning in the form of pretrained language models has become ubiquitous in NLP and has contributed to the state of the art on a wide range of tasks. However, transfer learning is not a recent phenomenon in NLP.

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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. These components are critical for understanding metaphors, which are prevalent in daily communication, literature, and scientific discourse.

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Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. The computational intensity required and the potential for various failures during extensive training periods necessitate innovative solutions for efficient management and recovery.

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NYU Center for Data Science

JULY 24, 2024

Ravfogel’s research focuses on understanding how neural networks learn distributed representations that encode structured information, and how these representations are utilized to solve complex tasks. This multidisciplinary foundation has informed his unique approach to computational linguistics and machine learning.

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NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. But what is the substance behind the buzz?

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Marek Rei

OCTOBER 4, 2019

The growth of interest in NLP technology, fuelled largely by investment in AI applications, has been accompanied by unprecedented expansion of the preeminent NLP conferences: ACL, NAACL and EMNLP in particular. Paper count by country at the 2018 NLP conferences. Normalized paper count by country at the 2018 NLP conferences.

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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.   Popularized by GPT-3 [32] , prompting has emerged as a viable alternative input format for NLP models.

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Ines Montani

MAY 9, 2017

Challenges for open-source NLP One of the biggest challenges for Natural Language Processing is dealing with fast-moving and unpredictable technologies. This is a lot less true in AI or NLP. Since spaCy was released, the best practices for NLP have changed considerably. to adding tokenizer exceptions for Bengali or Hebrew.

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AssemblyAI

SEPTEMBER 18, 2023

These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications. Engineers train these models on vast amounts of information. Reliability: LLMs can inadvertently generate false information or fake news.

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Allen AI

JULY 8, 2023

NLPositionality: Characterizing Design Biases of Datasets and Models Sebastin Santy, Jenny Liang, Ronan Le Bras*, Katharina Reinecke, Maarten Sap* Design biases in NLP systems, such as performance differences for different populations, often stem from their creator’s positionality, i.e., views and lived experiences shaped by identity and background.

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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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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). 4 ] Percentages of websites using various content languages (as of April 30, 2023).

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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). BERT is a new milestone in NLP.

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Explosion

DECEMBER 28, 2019

Jan 15: The year started out with us as guests on the NLP Highlights podcast , hosted by Matt Gardner and Waleed Ammar of Allen AI. In the interview, Matt and Ines talked about Prodigy , where training corpora come from and the challenges of annotating data for an NLP system – with some ideas about how to make it easier. ?

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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. Spark NLP is a natural language processing library built on Apache Spark.

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Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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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.

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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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Sebastian Ruder

NOVEMBER 14, 2022

At the same time, a wave of NLP startups has started to put this technology to practical use. I will be focusing on topics related to natural language processing (NLP) and African languages as these are the domains I am most familiar with. This post takes a closer look at how the AI community is faring in this endeavour.

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Bugra Akyildiz

JULY 16, 2023

Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age. In this course, students will gain a thorough introduction to cutting-edge research in Deep Learning for NLP.

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Sebastian Ruder

JUNE 6, 2022

Seeing the emergence of such multilingual multimodal approaches is particularly encouraging as it is an improvement over the previous year’s ACL where multimodal approaches mainly dealt with English (based on an analysis of “multi-dimensional” NLP research we did for an ACL 2022 Findings paper ). Hershcovich et al.

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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. For example, the communicative intent can be to convey information, socialise or ask someone to do something.

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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. If a computer program is trained on enough data such that it can analyze, understand, and generate responses in natural language and other forms of content, it is called a Large Language Model (LLM).

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Sebastian Ruder

FEBRUARY 23, 2023

For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial.  Instead of learning module parameters directly, they can be generated using an auxiliary model (a hypernetwork) conditioned on additional information and metadata. We cover such methods for NLP in our EMNLP 2022 tutorial. These models are monoliths.

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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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Allen AI

MAY 30, 2023

We evaluate the approach using human evaluation: compared to four other baselines ClarifyDelphi produces more informative and more relevant questions. It would be more elegant to have a way to automatically predict when enough contextual information has been obtained and the system does not have to ask an additional question.

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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. In the main() function, you can call the run() function as shown in the following code.

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Mlearning.ai

FEBRUARY 6, 2023

This methodology has been used to provide explanations for sentiment classification, topic tagging, and other NLP tasks and could potentially work for chatbot-writing detection as well.

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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. It might be a bit too early for an informative answer, but what can students and professionals planning to move to Europe expect from personal and professional perspectives?

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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 people played around with them, many problems such as bias and mis-information became prevalent.

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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. Linguistic and demographic utility of different NLP applications ( Blasi et al., TyDi QA ( Clark et al.,

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The Stanford AI Lab Blog

JANUARY 21, 2022

self-supervised or cheaply supervised learning) has been the backbone of the many recent successes of foundation models 3 in NLP 4 5 6 7 8 9 and vision 10 11 12. Conference of the North American Chapter of the Association for Computational Linguistics. ↩ Devlin, J., Neural Information Processing Systems. ↩ Finn, C.,

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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. as these words do not make any sense to machines.

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Snorkel AI

JUNE 14, 2023

Timo Mertens is the Head of ML and NLP Products at Grammarly. What information do you want to include? That ranges all the way from analytical and computational linguists to applied research scientists, machine learning engineers, data scientists, product managers, designers, UX researchers, and so on.

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Snorkel AI

JUNE 14, 2023

Timo Mertens is the Head of ML and NLP Products at Grammarly. What information do you want to include? That ranges all the way from analytical and computational linguists to applied research scientists, machine learning engineers, data scientists, product managers, designers, UX researchers, and so on.

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Probably Approximately a Scientific Blog

JULY 13, 2015

As many other NLP tasks, this one is also difficult. We used other structured knowledge resources that contain exactly this kind of information, are much larger than WordNet and are frequently updated. Proceedings of the 14th conference on Computational linguistics-Volume 2. Association for Computational Linguistics.

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