Computational Linguistics, Large Language Models and ML

Seeking Faster, More Efficient AI? Meet FP6-LLM: the Breakthrough in GPU-Based Quantization for Large Language Models

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.

Large Language Models

Large Language Models LLM Computational Linguistics Artificial Intelligence

QoQ and QServe: A New Frontier in Model Quantization Transforming Large Language Model Deployment

Marktechpost

MAY 12, 2024

Quantization, a method integral to computational linguistics, is essential for managing the vast computational demands of deploying large language models (LLMs). It simplifies data, thereby facilitating quicker computations and more efficient model performance. Check out the Paper.

Large Language Models

Large Language Models Computational Linguistics Algorithm LLM

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

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.

Large Language Models

Large Language Models AI Research AI Researcher Computational Linguistics

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

Marktechpost

JANUARY 15, 2024

One persistent challenge is the translation of low-resource languages, which often need more substantial data for training robust models. Traditional translation models, primarily based on large language models (LLMs), perform well with languages abundant in data but need help with underrepresented languages.

Large Language Models

Large Language Models Data Scarcity Computational Linguistics Natural Language Processing

Uncertainty-Aware Language Agents are Changing the Game for OpenAI and LLaMA

Marktechpost

JANUARY 30, 2024

Language Agents represent a transformative advancement in computational linguistics. They leverage large language models (LLMs) to interact with and process information from the external world. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup.

Computational Linguistics

Computational Linguistics OpenAI Large Language Models LLM

Alibaba AI Group Propose AgentScope: A Developer-Centric Multi-Agent Platform with Message Exchange as its Core Communication Mechanism

Marktechpost

MARCH 2, 2024

The emergence of Large Language Models (LLMs) has notably enhanced the domain of computational linguistics, particularly in multi-agent systems. Join our 38k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Check out the Paper.

Computational Linguistics

Computational Linguistics Large Language Models AI AI

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. Check out the Paper and Project.

Chatbots

Chatbots Computational Linguistics Large Language Models LLM

Researchers at Stanford University Explore Direct Preference Optimization (DPO): A New Frontier in Machine Learning and Human Feedback

Marktechpost

APRIL 20, 2024

Exploring the synergy between reinforcement learning (RL) and large language models (LLMs) reveals a vibrant area of computational linguistics. Don’t Forget to join our 40k+ ML SubReddit For Content Partnership, Please Fill Out This Form Here. Also, don’t forget to follow us on Twitter.

Machine Learning

Machine Learning Computational Linguistics Large Language Models LLM

Researchers from the University of Washington and Allen Institute for AI Introduce Time Vectors: A Simple Tool to Customize Language Models to New Time Periods

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.

Computational Linguistics

Computational Linguistics Artificial Intelligence Artificial Intelligence Machine Learning

Alibaba Researchers Unveil Unicron: An AI System Designed for Efficient Self-Healing in Large-Scale Language Model Training

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. Check out the Paper. All credit for this research goes to the researchers of this project.

Computational Linguistics

Computational Linguistics Large Language Models LLM BERT

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. Also, don’t forget to follow us on Twitter.

Automation

Automation Computational Linguistics Large Language Models Natural Language Processing

Data Distillation Meets Prompt Compression: How Tsinghua University and Microsoft’s LLMLingua-2 Is Redefining Efficiency in Large Language Models Using Task-Agnostic Techniques

Marktechpost

MARCH 22, 2024

The team has proposed a truly innovative approach to address these challenges: a data distillation procedure designed to distill essential information from large language models (LLMs) without compromising crucial details. Check out the Paper. All credit for this research goes to the researchers of this project.

Large Language Models

Large Language Models Computational Linguistics ML Artificial Intelligence

This AI Paper Presents SliCK: A Knowledge Categorization Framework for Mitigating Hallucinations in Language Models Through Structured Training

Marktechpost

MAY 14, 2024

Research in computational linguistics continues to explore how large language models (LLMs) can be adapted to integrate new knowledge without compromising the integrity of existing information. Also, don’t forget to follow us on Twitter. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

Categorization

Categorization Computational Linguistics Large Language Models Machine Learning

This AI Paper Introduces a Novel Artificial Intelligence Approach in Precision Text Retrieval Using Retrieval Heads

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.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Computational Linguistics Data Extraction

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

Marktechpost

AUGUST 15, 2024

Given the intricate nature of metaphors and their reliance on context and background knowledge, MCI presents a unique challenge in computational linguistics. 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

Researchers at UC Santa Cruz Propose a Novel Text-to-Image Association Test Tool that Quantifies the Implicit Stereotypes between Concepts and Valence and Those in the Images

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. Check out the Paper and Project Page.

Computational Linguistics

Computational Linguistics Software Engineer Generative AI AI Researcher

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). Pre-trained models were applied in many different domains and started to be considered critical for ML research [1]. 8) ML for Science The architecture of AlphaFold 2.0. Credit for the title image: Liu et al.

NLP

NLP ML BERT Computational Linguistics

A Gentle Introduction to GPTs

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.

Auto-classification

Auto-classification Auto-complete Natural Language Processing NLP

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.

Natural Language Processing

Natural Language Processing Machine Learning Computational Linguistics NLP

The State of Multilingual AI

Sebastian Ruder

NOVEMBER 14, 2022

Beyond individual languages, researchers with affiliations in countries where such languages are spoken are similarly under-represented in both ML and NLP communities. Representation of African NLP Researchers in top ML and NLP venues. *: does not consider African authors working abroad.

Natural Language Processing

Natural Language Processing NLP Computational Linguistics BERT

How Grammarly strives for superhuman communication assistance

Snorkel AI

JUNE 14, 2023

Timo Mertens is the Head of ML and NLP Products at Grammarly. 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. A transcript of the talk follows. Thank you so much for having me.

Machine Learning

Machine Learning Natural Language Processing Data Scientist Computational Linguistics

How Grammarly strives for superhuman communication assistance

Snorkel AI

JUNE 14, 2023

Timo Mertens is the Head of ML and NLP Products at Grammarly. 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. A transcript of the talk follows. Thank you so much for having me.

Machine Learning

Machine Learning Natural Language Processing Data Scientist Computational Linguistics

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

AWS Machine Learning Blog

AUGUST 8, 2024

Webex’s focus on delivering inclusive collaboration experiences fuels their innovation, which uses artificial intelligence (AI) and machine learning (ML), to remove the barriers of geography, language, personality, and familiarity with technology. Its solutions are underpinned with security and privacy by design.

Generative AI

Generative AI LLM AI AI

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. Praveen Chamarthi is a Senior AI/ML Specialist with Amazon Web Services. He is passionate about AI/ML and all things AWS.

Software Engineer

Software Engineer Large Language Models Generative AI Computational Linguistics

Supporting Human-AI Collaboration in Auditing LLMs with LLMs

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.

Computational Linguistics

Computational Linguistics LLM Large Language Models Algorithm

Artificial Intelligence Zone

Seeking Faster, More Efficient AI? Meet FP6-LLM: the Breakthrough in GPU-Based Quantization for Large Language Models

QoQ and QServe: A New Frontier in Model Quantization Transforming Large Language Model Deployment

Trending Sources

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

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

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

Uncertainty-Aware Language Agents are Changing the Game for OpenAI and LLaMA

Alibaba AI Group Propose AgentScope: A Developer-Centric Multi-Agent Platform with Message Exchange as its Core Communication Mechanism

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

Researchers at Stanford University Explore Direct Preference Optimization (DPO): A New Frontier in Machine Learning and Human Feedback

Researchers from the University of Washington and Allen Institute for AI Introduce Time Vectors: A Simple Tool to Customize Language Models to New Time Periods

Alibaba Researchers Unveil Unicron: An AI System Designed for Efficient Self-Healing in Large-Scale Language Model Training

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

Data Distillation Meets Prompt Compression: How Tsinghua University and Microsoft’s LLMLingua-2 Is Redefining Efficiency in Large Language Models Using Task-Agnostic Techniques

This AI Paper Presents SliCK: A Knowledge Categorization Framework for Mitigating Hallucinations in Language Models Through Structured Training

This AI Paper Introduces a Novel Artificial Intelligence Approach in Precision Text Retrieval Using Retrieval Heads

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

Researchers at UC Santa Cruz Propose a Novel Text-to-Image Association Test Tool that Quantifies the Implicit Stereotypes between Concepts and Valence and Those in the Images

ML and NLP Research Highlights of 2021

A Gentle Introduction to GPTs

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

The State of Multilingual AI

How Grammarly strives for superhuman communication assistance

How Grammarly strives for superhuman communication assistance

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

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

Supporting Human-AI Collaboration in Auditing LLMs with LLMs

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