Marktechpost

MARCH 12, 2024

The advent of large language models (LLMs) has ushered in a new era in computational linguistics, significantly extending the frontier beyond traditional natural language processing to encompass a broad spectrum of general tasks.

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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. Training these models, however, is challenging.

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Marktechpost

DECEMBER 26, 2023

Computational linguistics focuses on developing advanced language models capable of understanding and generating human language. This dynamic field integrates the latest in machine learning and artificial intelligence, striving to create models that grasp the intricacies of language.

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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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Marktechpost

JANUARY 22, 2024

Its innovative techniques and optimizations make it a standout performer, capable of handling large-scale language understanding tasks with remarkable speed and reliability. As technology advances, solutions like Marlin play an important role in pushing the boundaries of what’s possible in computational linguistics.

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Marktechpost

APRIL 29, 2024

In computational linguistics, much research focuses on how language models handle and interpret extensive textual data. These models are crucial for tasks that require identifying and extracting specific information from large volumes of text, presenting a considerable challenge in ensuring accuracy and efficiency.

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Marktechpost

AUGUST 12, 2023

This innovative tool was presented at the 2023 Association for Computational Linguistics (ACL) conference. Its primary purpose is quantifying and identifying biases within advanced generative models, like Stable Diffusion, which can magnify existing prejudices in the images generated.

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ODSC - Open Data Science

APRIL 3, 2023

In particular, we fine-tune a re-ranker model using only the relevant feedback from each query and obtained large performance gains in multiple domains, including news and COVID. Lastly, we are currently working on integrating recent works on Large Language Models such as ChatGPT. Euro) in 2021.

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Marktechpost

FEBRUARY 2, 2024

In computational linguistics and artificial intelligence, researchers continually strive to optimize the performance of large language models (LLMs). These models, renowned for their capacity to process a vast array of language-related tasks, face significant challenges due to their expansive size.

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The Stanford AI Lab Blog

MAY 25, 2022

The 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022 is taking place May 22nd - May 27th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below.

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Topbots

JANUARY 30, 2023

In the last couple of years, Large Language Models (LLMs) such as ChatGPT, T5 and LaMDA have developed amazing skills to produce human language. We are quick to attribute intelligence to models and algorithms, but how much of this is emulation, and how much is really reminiscent of the rich language capability of humans?

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Large Language Models LLM Computational Linguistics Natural Language Processing 52

John Snow Labs

DECEMBER 26, 2023

The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). The post Testing the Robustness of LSTM-Based Sentiment Analysis Models appeared first on John Snow Labs. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. Learning Word Vectors for Sentiment Analysis.

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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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AWS Machine Learning Blog

MAY 22, 2023

Increasingly capable foundation models are being released continuously, with large language models (LLMs) being one of the most visible model classes. LLMs are models composed of billions of parameters trained on extensive corpora of text, up to hundreds of billions or even a trillion tokens.

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Bugra Akyildiz

JULY 16, 2023

In here, the distinction is that base models want to complete documents(with a given context) where assistant models can be used/tricked into performing tasks with prompt engineering. Large language models (LLMs) have shown promise in proving formal theorems using proof assistants such as Lean.

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Mlearning.ai

FEBRUARY 19, 2023

Natural Language Processing (NLP) NLP is subset of Artificial Intelligence that is concerned with helping machines to understand the human language. It combines techniques from computational linguistics, probabilistic modeling, deep learning to make computers intelligent enough to grasp the context and the intent of the language.

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Topbots

JUNE 15, 2023

Large language models such as ChatGPT process and generate text sequences by first splitting the text into smaller units called tokens. Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. Shijie Wu and Mark Dredze.

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Sebastian Ruder

NOVEMBER 14, 2022

Cross-lingual performance prediction [42] could be used to estimate performance for a broader set of languages. Multilingual vs English-centric models   Let us now take a step back and look at recent large language models in NLP in general. Computational linguistics, 47(2), 255-308. Winata, G.

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Flipboard

SEPTEMBER 7, 2023

One of the best-known critiques of AI large language models, or LLMs, for example, compares AI’s lack of language understanding to that of an animal: the concept of the “stochastic parrot,” which refers to how chatbots, not having minds, spit out language based on probabilistic models with no regard for meaning.

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Sebastian Ruder

JANUARY 24, 2022

  One of the most notable applications of large language models this year was code generation, which saw with Codex [79] its first integration into a major product as part of GitHub Copilot. Other advances in pre-training models ranged from better pre-training objectives [80] [81] to scaling experiments [82] [83].

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Snorkel AI

JUNE 14, 2023

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. It’s clear how technology can help us in the advent of generative large language models.

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Snorkel AI

JUNE 14, 2023

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. It’s clear how technology can help us in the advent of generative large language models.

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ML @ CMU

SEPTEMBER 22, 2023

Illustration depicting the process of a human and a large language model working together to find failure cases in a (not necessarily different) large language model. Trends Human Computer Interaction. [2] Adaptive Testing and Debugging of NLP Models. 2] Marco Tulio Ribeiro and Scott Lundberg.

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ODSC - Open Data Science

MARCH 6, 2024

REGISTER NOW Building upon the exponential advancements in Deep Learning, Generative AI has attained mastery in Natural Language Processing. The driving force behind Generative AI and Large Language Models (LLMs) is Language Modeling, a Natural Language Processing technique that predicts the next word in a sequence of words.

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