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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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Meet Sailor: A Suite of Open Language Models for Bridging Linguistic Barriers in Southeast Asia

Marktechpost

In the ever-evolving landscape of computational linguistics, bridging language barriers has led to remarkable innovations, particularly in regions characterized by a rich tapestry of languages. Southeast Asia, with its linguistic diversity, presents a unique challenge for language technology.

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

Marktechpost

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. The QoQ algorithm utilizes a two-stage quantization process.

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Bigram Models Simplified

Towards AI

There are many text generation algorithms that can be classified as deep learning-based methods (deep generative models) and probabilistic methods. They serve as the building blocks for more complex models and algorithms in the field of computational linguistics.

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ACL vs TACL Reviewing

Ehud Reiter

At any rate, the reviewer set is mostly created algorithmically, but SACs can adjust it (I added several people who were conscientious and knowledgable but not suggested by the algorithm). The choice is done manually, not algorithmically. Every paper is assigned to three reviewers and an Area Chair. Review process?

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Natural Language Processing in Python: 10+ Packages You Can’t Miss (with Code)

Towards AI

It combines statistics and mathematics with computational linguistics. NLTK serves various purposes including text preprocessing, translation, and NLP tasks such as text classification, utilizing a multitude of implemented algorithms. stars on GitHub.

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AI2 at ACL 2023

Allen AI

This research posits that simply scaling up models will not imbue them with theory of mind due to the inherently symbolic and implicit nature of the phenomenon, and instead investigate an alternative: can we design a decoding-time algorithm that enhances theory of mind of off-the-shelf neural language models without explicit supervision?