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68 Summaries of Machine Learning and NLP Research

Marek Rei

They show state-of-the-art results on long-context language modelling, finding a hidden passcode from a 1M token length context, and summarizing 500K length books. BooookScore: A systematic exploration of book-length summarization in the era of LLMs Yapei Chang, Kyle Lo, Tanya Goyal, Mohit Iyyer. Computational Linguistics 2022.

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ML and NLP Research Highlights of 2021

Sebastian Ruder

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). If CNNs are pre-trained the same way as transformer models, they achieve competitive performance on many NLP tasks [28].   Popularized by GPT-3 [32] , prompting has emerged as a viable alternative input format for NLP models.

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All Languages Are NOT Created (Tokenized) Equal

Topbots

Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. 70% of research papers published in a computational linguistics conference only evaluated English.[ Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold.

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Google at ACL 2023

Google Research AI blog

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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ChatGPT4 still leads ChatBot/LLM Leaderboard

Bugra Akyildiz

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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The State of Multilingual AI

Sebastian Ruder

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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Modular Deep Learning

Sebastian Ruder

For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial. Fixed routing can select different modules for different aspects of the target setting such as task and language in NLP or robot and task in RL, which enables generalisation to unseen scenarios. We cover such methods for NLP in our EMNLP 2022 tutorial.