To Data & Beyond Week 17 Summary

Every week, To Data & Beyond delivers daily newsletters on data science and AI, focusing on practical topics. This newsletter summarizes the featured article in the seventeenth week of 2024. You can find them here if you're interested in reading the complete letters. Don't miss out—subscribe here to receive them directly in your email.

Table of Contents:

1. Top Important Computer Vision Papers for the Week from 15/04 to 21/04
2. Top Important LLM Papers for the Week from 15/04 to 21/04
3. Best Resources to Learn & Understand Evaluating LLMs
4. Building LLM Agents Using LangChain & OpenAI API
5. Building Chatbot Using HuggingFace Open Source Models

1. Top Important Computer Vision Papers for the Week from 15/04 to 21/04

Every week, several top-tier academic conferences and journals showcased innovative research in computer vision, presenting exciting breakthroughs in various subfields such as image recognition, vision model optimization, generative adversarial networks (GANs), image segmentation, video analysis, and more.

This article provides a comprehensive overview of the most significant papers published in the Third Week of April 2024, highlighting the latest research and advancements in computer vision.

Whether you’re a researcher, practitioner, or enthusiast, this article will provide valuable insights into the state-of-the-art techniques and tools in computer vision.

You can continue reading this letter from here

2. Top Important LLM Papers for the Week from 15/04 to 21/04

Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. This article summarizes some of the most important LLM papers published during the Third Week of April 2024.

The papers cover various topics shaping the next generation of language models, from model optimization and scaling to reasoning, benchmarking, and enhancing performance. Keeping up with novel LLM research across these domains will help guide continued progress toward models that are more capable, robust, and aligned with human values.

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3. Best Resources to Learn & Understand Evaluating LLMs

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications.?

As LLMs continue to play a vital role in both research and daily use, their evaluation becomes increasingly critical, not only at the task level but also at the societal level for a better understanding of their potential risks. Over the past years, significant efforts have been made to examine LLMs from various perspectives.?

This article presents a comprehensive set of resources that will help you understand LLM evaluation starting from what to evaluate, where to evaluate, and how to evaluate.

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4. Building LLM Agents Using LangChain & OpenAI API

When we think about large language models (LLM), we often imagine them as super-smart databases filled with internet knowledge, ready to answer any question we throw at them. But the reality is that they are clever assistants, able to understand what we tell them and help us figure things out.

That’s where LangChain’s Agents come in. It’s like giving your assistant superpowers! In agents, a language model is used as a reasoning engine to determine which actions to take and in which order.

In this guide, we’ll dive into what agents are, how to make them, and how to teach them to do all sorts of neat tricks, like searching Wikipedia, solving programming questions, and finally building your own agent.

You can continue reading this letter from here

5. Building Chatbot Using HuggingFace Open Source Models

Hugging Face is a platform that hosts a treasure trove of open-source models, making it a goldmine for anyone diving into the world of natural language processing. In this guide, I walk you through the process of building your very own chatbot using an open-source model on HuggingFace.?

I start by setting up your working environment, ensuring you’re armed with all the necessary tools to embark on this exciting journey. With the Transformers library at our disposal, we delve into creating a conversational pipeline, leveraging the Pipeline function to streamline the process.

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