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NLEPs: Bridging the gap between LLMs and symbolic reasoning

AI News

The research, supported in part by the Center for Perceptual and Interactive Intelligence of Hong Kong, will be presented at the Annual Conference of the North American Chapter of the Association for Computational Linguistics later this month. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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A Guide to Computational Linguistics and Conversational AI

Towards AI

if this statement sounds familiar, you are not foreign to the field of computational linguistics and conversational AI. In this article, we will dig into the basics of Computational Linguistics and Conversational AI and look at the architecture of a standard Conversational AI pipeline.

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

Marktechpost

Tokenization is essential in computational linguistics, particularly in the training and functionality of large language models (LLMs). Researchers from Cohere introduce a novel approach that utilizes the model’s embedding weights to automate and scale the detection of under-trained tokens.

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

Marktechpost

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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Best Large Language Models & Frameworks of 2023

AssemblyAI

These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications. They tended to rely on smaller datasets and more developer handholding, making them less intelligent and more like automation tools.

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68 Summaries of Machine Learning and NLP Research

Marek Rei

They focus on coherence, as opposed to correctness, and develop an automated LLM-based score (BooookScore) for assessing summaries. They first have humans assess each sentence of a sample of generated summaries, then check that the automated metric correlates with the human assessment. Computational Linguistics 2022.

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DL4Proteins Notebook Series Bridging Machine Learning and Protein Engineering: A Practical Guide to Deep Learning Tools for Protein Design

Marktechpost

The notebook guides users through creating, training, and evaluating models, highlighting how PyTorch automates key tasks like gradient computation and optimization. It simplifies implementing neural networks by leveraging PyTorch’s high-level abstractions, such as tensors, autograd, and modules.