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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.[ Association for Computational Linguistics.

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NLP Landscape: Germany (Industry & Meetups)

NLP People

spaCy spaCy is an open-source software library for advanced industrial-strength NLP, created by Explosion AI, a digital studio specialising in Artificial Intelligence and Natural Language Processing. They are hiring. They are not hiring at the moment, but you can always drop them a line.

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Large Language Models – Technical Overview

Viso.ai

LLMs are pre-trained on extensive data on the web which shows results after comprehending complexity, pattern, and relation in the language. LLMs apply powerful Natural Language Processing (NLP), machine translation, and Visual Question Answering (VQA).

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Overcoming The Limitations Of Large Language Models

Topbots

In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages 5185–5198, Online. Association for Computational Linguistics. [2] Injecting Domain Knowledge in Language Models for Task-Oriented Dialogue Systems. SKILL: Structured Knowledge Infusion for Large Language Models.

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The State of Multilingual AI

Sebastian Ruder

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. In Findings of the Association for Computational Linguistics: ACL 2022 (pp. 2340–2354). Winata, G.

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Modular Deep Learning

Sebastian Ruder

We first highlight common applications in NLP and then draw analogies to applications in speech, computer vision, and other areas of machine learning. Computer vision and cross-modal learning. In computer vision, common module choices are adapters and subnetworks based on ResNet or Vision Transformer models.

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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). In computer vision, supervised pre-trained models such as Vision Transformer [2] have been scaled up [3] and self-supervised pre-trained models have started to match their performance [4]. Schneider, R.,

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