Computational Linguistics, Large Language Models and Natural Language Processing

Computational Linguistics

Large Language Models

Natural Language Processing

Leveraging Linguistic Expertise in NLP: A Deep Dive into RELIES and Its Impact on Large Language Models

Marktechpost

MAY 11, 2024

With the significant advancement in the fields of Artificial Intelligence (AI) and Natural Language Processing (NLP), Large Language Models (LLMs) like GPT have gained attention for producing fluent text without explicitly built grammar or semantic modules. If you like our work, you will love our newsletter.

Large Language Models

Large Language Models NLP Data Scarcity Computational Linguistics

Best Large Language Models & Frameworks of 2023

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.

Large Language Models

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Do Large Language Models Really Need All Those Layers? This AI Research Unmasks Model Efficiency: The Quest for Essential Components in Large Language Models

Marktechpost

JULY 15, 2023

The advent of large language models (LLMs) has sparked significant interest among the public, particularly with the emergence of ChatGPT. These models, which are trained on extensive amounts of data, can learn in context, even with minimal examples. Strikingly, even after removing up to 70% (around 15.7

Large Language Models

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This AI Paper from Apple Unveils AlignInstruct: Pioneering Solutions for Unseen Languages and Low-Resource Challenges in Machine Translation

Marktechpost

JANUARY 15, 2024

Machine translation, an integral branch of Natural Language Processing, is continually evolving to bridge language gaps across the globe. One persistent challenge is the translation of low-resource languages, which often need more substantial data for training robust models.

Large Language Models

Large Language Models Data Scarcity Computational Linguistics Natural Language Processing

Chatbot Arena: An Open Platform for Evaluating LLMs through Crowdsourced, Pairwise Human Preferences

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.

Chatbots

Chatbots Computational Linguistics Large Language Models LLM

This AI Paper from Cohere Enhances Language Model Stability with Automated Detection of Under-trained Tokens in LLMs

Marktechpost

MAY 13, 2024

Tokenization is essential in computational linguistics, particularly in the training and functionality of large language models (LLMs). This process involves dissecting text into manageable pieces or tokens, which is foundational for model training and operations. Check out the Paper.

Automation

Automation Computational Linguistics Large Language Models Natural Language Processing

Large Language Models – Technical Overview

Viso.ai

JULY 18, 2024

What are Large Language Models (LLMs)? In generative AI, human language is perceived as a difficult data type. 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).

Large Language Models

Large Language Models Neural Network Natural Language Processing BERT

Overcoming The Limitations Of Large Language Models

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?

Large Language Models

Large Language Models Computational Linguistics LLM Natural Language Processing

SQuARE: Towards Multi-Domain and Few-Shot Collaborating Question Answering Agents

ODSC - Open Data Science

APRIL 3, 2023

Question Answering is the task in Natural Language Processing that involves answering questions posed in natural language. The goal of QA is to create models that can understand the nuances of a question and some given evidence documents to provide an accurate and concise answer. Haritz Puerto is a Ph.D.

Neural Network

Neural Network Natural Language Processing NLP Computational Linguistics

Linguistics-aware In-context Learning with Data Augmentation (LaiDA): An AI Framework for Enhanced Metaphor Components Identification in NLP Tasks

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. This framework leverages the power of large language models (LLMs) like ChatGPT to improve the accuracy and efficiency of MCI.

NLP

NLP Large Language Models Computational Linguistics Neural Network

Google at ACL 2023

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.

Large Language Models

Large Language Models Natural Language Processing NLP Computational Linguistics

All Languages Are NOT Created (Tokenized) Equal

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. As ChatGPT and similar models are becoming increasingly integrated into products and services worldwide, it is crucial to understand and address such inequalities.

Natural Language Processing

Natural Language Processing Computational Linguistics NLP ChatGPT

A Gentle Introduction to GPTs

Mlearning.ai

FEBRUARY 19, 2023

You don’t need to have a PhD to understand the billion parameter language model GPT is a general-purpose natural language processing model that revolutionized the landscape of AI. GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . What is GPT-3?

Auto-classification

Auto-classification Auto-complete Natural Language Processing NLP

ChatGPT4 still leads ChatBot/LLM Leaderboard

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.

LLM

LLM Chatbots Neural Network Large Language Models

68 Summaries of Machine Learning and NLP Research

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. It is probably good to also to mention that I wrote all of these summaries myself and they are not generated by any language models. Here we go. NeurIPS 2023. ArXiv 2024.

Machine Learning

Machine Learning NLP Large Language Models LLM

Instruction fine-tuning for FLAN T5 XL with Amazon SageMaker Jumpstart

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.

Machine Learning

Machine Learning Natural Language Processing Computational Linguistics NLP

The State of Multilingual AI

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. Cross-lingual performance prediction [42] could be used to estimate performance for a broader set of languages.

Natural Language Processing

Natural Language Processing NLP Computational Linguistics BERT

Testing the Robustness of LSTM-Based Sentiment Analysis Models

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. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). Daly, Peter T.

Neural Network

Neural Network Computational Linguistics NLP Natural Language Processing

ML and NLP Research Highlights of 2021

Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). 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. De Sa, C.,

NLP

NLP ML BERT Computational Linguistics

How Grammarly strives for superhuman communication assistance

Snorkel AI

JUNE 14, 2023

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. We take that writing and pre-process that.

Machine Learning

Machine Learning Natural Language Processing Data Scientist Computational Linguistics

How Grammarly strives for superhuman communication assistance

Snorkel AI

JUNE 14, 2023

Machine Learning

Machine Learning Natural Language Processing Data Scientist Computational Linguistics

Cisco achieves 50% latency improvement using Amazon SageMaker Inference faster autoscaling feature

AWS Machine Learning Blog

AUGUST 8, 2024

In the past year, the team has increasingly focused on building artificial intelligence (AI) capabilities powered by large language models (LLMs) to improve productivity and experience for users. Karthik Raghunathan is the Senior Director for Speech, Language, and Video AI in the Webex Collaboration AI Group.

Software Engineer

Software Engineer Large Language Models Generative AI Computational Linguistics

How Cisco accelerated the use of generative AI with Amazon SageMaker Inference

AWS Machine Learning Blog

AUGUST 8, 2024

Cisco’s Webex AI (WxAI) team plays a crucial role in enhancing these products with AI-driven features and functionalities, using large language models (LLMs) to improve user productivity and experiences. Karthik Raghunathan is the Senior Director for Speech, Language, and Video AI in the Webex Collaboration AI Group.

Generative AI

Generative AI LLM AI AI

Language Modeling, Ethical Considerations of Generative AI, and Responsible AI

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.

Responsible AI

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Artificial Intelligence Zone

Leveraging Linguistic Expertise in NLP: A Deep Dive into RELIES and Its Impact on Large Language Models

Best Large Language Models & Frameworks of 2023

Webinars

Trending Sources

Do Large Language Models Really Need All Those Layers? This AI Research Unmasks Model Efficiency: The Quest for Essential Components in Large Language Models

Webinars

This AI Paper from Apple Unveils AlignInstruct: Pioneering Solutions for Unseen Languages and Low-Resource Challenges in Machine Translation

Chatbot Arena: An Open Platform for Evaluating LLMs through Crowdsourced, Pairwise Human Preferences

This AI Paper from Cohere Enhances Language Model Stability with Automated Detection of Under-trained Tokens in LLMs

Large Language Models – Technical Overview

Overcoming The Limitations Of Large Language Models

SQuARE: Towards Multi-Domain and Few-Shot Collaborating Question Answering Agents

Linguistics-aware In-context Learning with Data Augmentation (LaiDA): An AI Framework for Enhanced Metaphor Components Identification in NLP Tasks

Google at ACL 2023

All Languages Are NOT Created (Tokenized) Equal

A Gentle Introduction to GPTs

ChatGPT4 still leads ChatBot/LLM Leaderboard

68 Summaries of Machine Learning and NLP Research

Instruction fine-tuning for FLAN T5 XL with Amazon SageMaker Jumpstart

The State of Multilingual AI

Testing the Robustness of LSTM-Based Sentiment Analysis Models

ML and NLP Research Highlights of 2021

How Grammarly strives for superhuman communication assistance

How Grammarly strives for superhuman communication assistance

Cisco achieves 50% latency improvement using Amazon SageMaker Inference faster autoscaling feature

How Cisco accelerated the use of generative AI with Amazon SageMaker Inference

Language Modeling, Ethical Considerations of Generative AI, and Responsible AI

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