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SQuARE: Towards Multi-Domain and Few-Shot Collaborating Question Answering Agents

ODSC - Open Data Science

Or do you want to compare the capabilities of ChatGPT against regular fine-tuned QA models? Moreover, combining expert agents is an immensely easier task to learn by neural networks than end-to-end QA. Lastly, we are currently working on integrating recent works on Large Language Models such as ChatGPT. Euro) in 2021.

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CDS Faculty Member Tim G.

NYU Center for Data Science

The paper will be presented at the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL2025). The funding will support both computational resources for working with frontier AI models and personnel to assist with Rudners research.

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

Marktechpost

Given the intricate nature of metaphors and their reliance on context and background knowledge, MCI presents a unique challenge in computational linguistics. Neural network models based on word embeddings and sequence models have shown promise in enhancing metaphor recognition capabilities.

NLP 60
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Explainable AI and ChatGPT Detection

Mlearning.ai

When ChatGPT was last November, it took the world by storm. But despite this hype, educators around the world immediately saw a huge problem: students using ChatGPT for their homework and essays. Classifiers based on neural networks are known to be poorly calibrated outside of their training data [3].

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Large Language Models – Technical Overview

Viso.ai

With the advent of platforms like ChatGPT, these terms have now become a word of mouth for everyone. Emergence and History of LLMs Artificial Neural Networks (ANNs) and Rule-based Models The foundation of these Computational Linguistics models (CL) dates back to the 1940s when Warren McCulloch and Walter Pitts laid the groundwork for AI.

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2022: We reviewed this year’s AI breakthroughs

Applied Data Science

Dall-e , and pre-2022 tools in general, attributed their success either to the use of the Transformer or Generative Adversarial Networks. The former is a powerful architecture for artificial neural networks that was originally introduced for language tasks (you’ve probably heard of GPT-3 ?) Who should I follow? What happened?

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ChatGPT4 still leads ChatBot/LLM Leaderboard

Bugra Akyildiz

ChatRWKV is like ChatGPT but powered by my RWKV (100% RNN) language model, which is the only RNN (as of now) that can match transformers in quality and scaling, while being faster and saves VRAM. Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age.

LLM 52