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In this video, we dive into the groundbreaking DeepSeek-R1 research paper, titled "DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning". This paper introduces the models DeepSeek-R1-Zero and DeepSeek-R1, open-source reasoning models that rivals the performance of top-tier models like OpenAI's o1! Here's a quick ...

Interpreting and running standardized language model benchmarks and evaluation datasets for both generalized and task specific performance assessments! Resources: lm-evaluation-harness: https://github.com/EleutherAI/lm-evaluation-harness lm-evaluation-harness setup script: https://drive.google.com/file/d/1oWoWSBUdCiB82R-8m52nv_-5pylXEcDp/view ...

Paper reading in the Discord group. All the lecture was improvised. Join the group: https://discord.gg/JRKsaNbhCg Link to paper: https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf

Discover how to build an intelligent book recommendation system using the power of large language models and Python. Learn to transform book descriptions into mathematical representations that enable precise content-based matching. By the end of this course, you'll have built a recommendation engine that helps readers discover their next ...

Let’s explore the DeepSeek LLM research paper! Discover how DeepSeek, an open-source AI model, processes information to solve complex problems in math, coding, and more: https://patentbusinesslawyer.com/deepseek-api-documentation-guide-building-innovations/ Trained on an astonishing 2 trillion words, DeepSeek not only surpasses models like ...

In this video, I discuss the challenges of working with PDFs for LLM applications and introduce you to an open-source tool called Marker. Marker simplifies the conversion of complex PDF files into structured Markdown, making data extraction much easier. I compare Marker with NuGet, showing its superior performance in preserving document ...

In this exciting tutorial, we'll dive into the world of Generative AI and create a powerful PDF summarization app using the cutting-edge language model, LaMini-LM. With the help of Streamlit, a user-friendly Python library, we'll build an intuitive web interface that allows you to effortlessly summarize PDF documents with just a few clicks. To ...

In this video, we learn how to summarize PDFs easily using LLMs and LangChain in Python. 📚 Programming Books & Merch 📚 🐍 The Python Bible Book: https://www.neuralnine.com/books/ 💻 The Algorithm Bible Book: https://www.neuralnine.com/books/ 👕 Programming Merch: https://www.neuralnine.com/shop 💼 Services 💼 💻 Freelancing ...

📖Paper: https://dapo-sia.github.io/static/pdf/dapo_paper.pdf 🐈‍⬛Github: https://github.com/BytedTsinghua-SIA/DAPO 🏫Institutes: ByteDance Seed, Tsinghua University LLM Reinforcement Learning: DAPO Unlocks the Black Box! This research introduces the Decoupled Clip and Dynamic Sampling Policy Optimization (DAPO) algorithm, an open ...

In this lecture, we understand the basics of LLMs: (1) Introduction (2) Significance of the word “Large” in Large Language Models (3) LLMs vs Earlier NLP Models (4) LLM Secret Sauce: Transformers (5) Difference between the terminologies: LLM vs GenAI vs DL vs ML vs AI (6) Applications of LLMs The key reference book which this video series ...

This is a rundown of the best NLP, Transformers and LLM papers of 2024. The papers in this video cover a wide range of disciplines - from core deep learning research, novel tokenization schemes, resurrecting RNNs, building on the Mamba architecture, to the latest prompting techniques for efficient retrieval, continual learning, and maximizing ...

This video is a step-by-step easy demo of Unstract, an open-source, no-code platform that helps you automate complex business processes involving long, complicated documents with a human in the loop by leveraging LLMs. Unstract goes beyond what current IDP (Intelligent Document Processing) and RPA (Robotic Process Automation) systems are ...

Large Language Model Agents have taken over LLM and Artificial Intelligence application design by storm, so this time we check out and simplify six main concepts and five popular papers documenting ways to set up language model based agents, as well as directly testing examples. Resources - @LangChain Agent Tutorials & Code - https://www ...

Watch my colleague Jonathan Larson present on GraphRAG! GraphRAG is a research project from Microsoft exploring the use of knowledge graphs and large language models for enhanced retrieval augmented generation. It is an end-to-end system for richly understanding text-heavy datasets by combining text extraction, network analysis, LLM prompting ...

Join us as we discuss the latest research from OpenAI and Anthropic. We’re excited to chat about this significant step forward in understanding how LLMs work and the implications it has for deeper understanding of the neural activity of language models. Hope you can join the conversation! Open AI’s Paper: https://openai.com/index/extracting ...

Threat intelligence is replete with challenges, necessitating a large experience, knowledge, and techniques to really understand the threat landscape, the TTPs, and to accurately track threat actors. Given this context, it is crucial to innovate and introduce the tools and techniques to both the current and next generation of analysts who stand ...

How can one best use extra FLOPS at test time? Paper: https://arxiv.org/abs/2408.03314 Abstract: Enabling LLMs to improve their outputs by using more test-time computation is a critical step towards building generally self-improving agents that can operate on open-ended natural language. In this paper, we study the scaling of inference-time ...

I tested my local, small LLM connected to my Zotero database in Open WebUI against NotebookLM. The results were really, truly surprising. Please Like and Subscribe to support the channel! @LearnMetaAnalysis I tested Granite 3.1-2b and Granite 3.1-8b vs NotebookLM. I am now more impressed than ever! If you find Granite hallucinating with the ...

PDFs are essential in business, academics, and more for their consistent formatting, but extracting content can be tricky, especially with images, tables, and formulas. This is a key step in preparing text for RAG (Retrieval-Augmented Generation) applications and language models (LLMs). In this video, we’ll show you how converting PDFs to ...

This video provides a step-by-step guide to help you learn how to use Large Language Models (LLMs) to extract data from PDFs and convert it into JSON format. The tutorial covers prompt engineering techniques and practical implementation steps. ℹ️ DIFFERENT CHAPTERS 0:00 - Introduction 00:42 - Use case workflow 1:56 - Usec case data and ...

Implementing multiple memory systems into Language Model Agents! Resources: Agentic Memory Repo - https://github.com/ALucek/agentic-memory/tree/main Types of Memory - https://www.psychologytoday.com/us/basics/memory/types-of-memory Cognitive Architectures for Language Agents - https://arxiv.org/pdf/2309.02427 A Survey on the Memory Mechanism of ...

In this tutorial, I delve into the intricacies of evaluating large language models (LLMs) using the versatile Evaluation Harness tool. Explore how to rigorously test LLMs across diverse datasets and benchmarks, including HellaSWAG, TruthfulQA, Winogrande, and more. This video features the LLaMA 3 model by Meta AI and demonstrates step-by-step ...

We present AutoGen, an open-source framework that allows developers to build LLM applications by composing multiple agents to converse with each other to accomplish tasks. AutoGen agents are customizable, conversable, and can operate in various modes that employ combinations of LLMs, human inputs, and tools. It also enables developers to create ...

Check out HubSpot's FREE AI Prompt Library Now! https://clickhubspot.com/h14h In this video, I will be going through (more than) 10 research papers in the field of AI/ML with the most citations in the year 2024. My AI papers newsletter https://mail.bycloud.ai/ Check out my Patreon for the full list https://www.patreon.com/c/bycloud https://www ...

Large Language Models: A Survey https://arxiv.org/pdf/2402.06196.pdf Andrej Karpathy LLM Paper Reading List for LLM Mastery https://medium.com/towards-artificial-intelligence/andrej-karpathy-llm-paper-reading-list-for-llm-mastery-89e751ad0cc1?sk=de202ac6d46f4d13343458fe6e900eb0 ...

The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series on LLMs. In this more practical followup, I take you through the many ways I use LLMs in my own life. Chapters 00:00:00 Intro into the growing LLM ecosystem 00:02:54 ChatGPT interaction ...

Paper: https://arxiv.org/pdf/2411.10541.pdf This research paper investigates the impact of prompt formatting on the performance of OpenAI's GPT language models. The authors tested various formats (plain text, Markdown, JSON, YAML) across multiple tasks and datasets, finding significant performance variations, especially in smaller models like ...

Support me on Patreon where you can tell me what AI paper you want me to cover next! https://www.patreon.com/jacksee/membership Paper: LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings Conclusion: This paper introduces TEA-GLM, a framework that enhances zero-shot learning in graph machine learning by ...

Join me as I explore the ground-breaking advancements of Med-Gemini in the field of medical AI. In this video, I dive into some of the key findings and insights from the latest research, highlighting how Med-Gemini is setting new benchmarks in clinical reasoning, multimodal understanding, and long-context processing. Discover how these ...

System Design Course at InterviewReady: https://interviewready.io/ This is how LLMs are scaling up their test compute time to deliver better results. 00:00 Agenda 00:20 Scaling Law 1.0 01:48 Using smaller weights 03:44 Increasing model training 06:05 Google Titans 07:40 What's after transformers? 08:45 Neuromorphic Computing References: 1.58 ...

LayoutLM: Pre-training of Text and Layout for Document Image Understanding," authored by Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, and Ming Zhou. The paper was presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP) in 2020. LayoutLM extends the pre-training of language models to incorporate both ...

REFERENCES: 1. Build an LLM from Scratch book: https://amzn.to/4fqvn0D 2. Build an LLM from Scratch repo: https://github.com/rasbt/LLMs-from-scratch 3. Slides: https://sebastianraschka.com/pdf/slides/2024-build-llms.pdf 4. LitGPT: https://github.com/Lightning-AI/litgpt 5. TinyLlama pretraining: https://lightning.ai/lightning-ai/studios/pretrain ...

This is an introduction to evaluating Large Language Models (LLMs), which covers what a dataset is, how we measure performance, and how automatic and human evaluation are done.

Support me on Patreon where you can tell me what AI paper you want me to cover next! https://www.patreon.com/jacksee/membership Paper: Large Language Model Meets Graph Neural Network in Knowledge Distillation Conclusion: In this paper, we propose a novel LLM-to-GNN knowledge distillation framework termed LinguGKD, which integrates the semantic ...

📖Paper: https://arxiv.org/abs/2501.09891 👥Authors: Kuang-Huei Lee, Ian Fischer, Yueh-Hua Wu, Dave Marwood, Shumeet Baluja, Dale Schuurmans, Xinyun Chen 🏫Institutes: Google DeepMind, UC San Diego, University of Alberta LLMs Evolving: Mind Evolution Makes Problem Solving a Breeze!🌀 This research introduces Mind Evolution, an ...

Join us as we unravel the complexities of large language models (LLM) by going through the Llama 3.1 paper! Learn how this groundbreaking research is shaping the future of Large Language Models (LLMs) while utilizing non-proprietary data for unparalleled performance. Whether you're a tech enthusiast or a seasoned AI professional, this video is ...

#deeplearning #largelanguagemodels #machinelearning Source Code: https://github.com/611noorsaeed/Research-Papers-Recommendation-System-and-Subject-Area-Prediction-Using-Deep-Learning-and-LLMS/blob/main/Research Paper recommendation and subject area prediction using sentence transformer.ipynb Download Save Files (Models): https://www.kaggle.com ...

Turns out reinforcement learning is all you need Check out my prior video on RL: https://youtu.be/qTY4Rr-x5q0?si=pgTpw9r9xwkuZJM6 Resources: Code: https://github.com/ALucek/GRPO-Training/tree/main Model: https://huggingface.co/AdamLucek/Qwen2.5-3B-Instruct-GRPO-2K-GSM8K DeepSeek-R1 Paper: https://arxiv.org/pdf/2501.12948 DeepSeek Math Paper ...

In this video, we break down DAPO: An Open-Source LLM Reinforcement Learning System at Scale — a new research paper from ByteDance that introduces DAPO (Decoupled Clip and Dynamic sAmpling Policy Optimization), a powerful reinforcement learning (RL) algorithm built on GRPO (Grouped Relative Policy Optimization). DAPO tackles key challenges in ...

A detailed breakdown of the AI research paper: CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation by Authors: Ruwei Pan, Hongyu Zhang, Chao Liu. Read the full article: https://arxiv.org/abs/2501.07811 Check out our free AI courses: https://theministryofai.org/courses-2/

This paper, "Large Language Models in Numberland," examines how well large language models (LLMs) understand and reason with numbers by introducing a test called "Numberland". The test includes problems ranging from basic math to more complex tasks like checking if a number is prime and playing the game of 24. The researchers found that while ...

Train a Large Language Model (LLM) on a set of pdf files to then ask questions about the content. In this example, we are training on instruction documents on how to file taxes, to then ask specific questions about tax filings. Learn how to use the LangChain package to build/train the appropriate index. code notebook: https://github.com ...

reviews the research paper "Agent Laboratory: Using LLM Agents as Research Assistants" by Schmidgall et al. Agent Laboratory is a novel research framework that leverages Large Language Model (LLM) agents to automate various stages of the research process, from idea exploration to report generation. The goal of the project is to empower ...

Title: Survey on Evaluation of LLM-based Agents (Mar 2025) Link: http://arxiv.org/abs/2503.16416v1 Date: March 2025 Summary: This paper provides the first comprehensive survey of evaluation methodologies for increasingly capable LLM-based agents. The survey analyzes evaluation benchmarks and frameworks across agent capabilities, application ...

This research paper explores multi-LLM-agent systems (MLAS), a new paradigm in artificial intelligence where multiple large language models (LLMs) act as autonomous agents, collaborating to solve complex tasks. The authors discuss the technical aspects of MLAS, including architecture, communication protocols, and agent training methods, while ...

Research Methodology || Important Questions || LLM-II || Kurukshetra University In this vlog, important questions on the subject of Research Methodology of LL.M IInd year of Kurukshetra University have been shared. This kind of vlog on other subjects have also been made available in the playlist of LL.M on this channel. Do subscribe, like and ...

Video contains detailed method of writing the longish term paper.

Join us for a comprehensive survey of techniques designed to unlock the full potential of Language Model Models (LLMs). Explore strategies such as fine-tuning, RAG (Retrieval-Augmented Generation), and prompt engineering to maximize LLM performance. Speakers: John Allard Engineering Lead, Fine-tuning Product Team at @OpenAI Colin Jarvis ...

The study "A Summative Assessment of Physical Concept Understanding" checks if **large language models (LLMs) truly grasp physical concepts** like gravity. The researchers used a method called summative assessment, which involves testing different levels of understanding. The assessment, called PHYSICO, has two parts: one tests basic knowledge ...

Simple and easy explanation of LLM or Large Language Model in less than 5 minutes. In this short video, you will build an intuition of how a large language model works using animation and simple story telling. This is the explanation that even a high school student can understand easily. Simple Explanation of Neural Network: https://www.youtube ...