We also provide example scripts for training and evaluation, for playing around with the Singular Value Finetuning (SVF) method introduced in Transformer² We hope this will be useful for researchers and developers interested in self-adaptive LLMs.
MACHINE LEARNING
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Correlation vs Causation: Key to Robust Generalization
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If your learning algorithm is based on correlation rather than causation, it will struggle with overfitting. To understand something is to identify its minimal sufficient causal mechanisms. Parsimony isn't just elegance, it's generalization robustness.
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Scaling LLMs: Long-Sequence Modeling and Distributed Training
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3/ Chapter 2: Generative Models Learn how LLMs are scaled for massive datasets
Discover long-sequence modeling & distributed training
Decode the scaling laws behind state-of-the-art models Build systems that go BIG! -
Pre-training Foundations: Self-supervised Learning and LLM Architectures
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2/ Chapter 1: Pre-training Foundations
Demystify self-supervised learning
Explore architectures like encoder-decoder models
See how pre-training powers scalability in AI Master the backbone of LLMs like BERT! -
Building LLMs: Comprehensive Guide to Architecture and Ethics
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1/ Why You Need This Book
Written by Tong Xiao & Jingbo Zhu of Northeastern University’s NLP Lab & NiuTrans Research, this 200+ page masterpiece dives into: How LLMs are built (like GPT & BERT) Advanced prompting techniques Ethical alignment strategies (RLHF)
Let’s -
Foundations of Large Language Models: Essential Blueprint for AI
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Day 6 – 25 Days of AI for ALL in 2025 The AI revolution is here, and to lead it, you need the best resources. Enter “Foundations of Large Language Models” by Tong Xiao & Jingbo Zhu—a 200+ page masterwork that just dropped on arXiv! Let’s dive into this blueprint for LLM
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Master Python Fundamentals: Ultimate Beginner’s Guide with Practice Questions
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"Master #Python Fundamentals: Ultimate Guide for Beginners" — The Number #1 Python Book For Beginners with 300+ Hands-on Practice Questions Brilliant book at http://
amzn.to/3QCQCDn by @RealBenjizo ————
#DataScience #DataScientist #MachineLearning #ComputationalScience #Coding -
CrystalGRW: Generative Modeling of Crystal Structures with Geodesic Random Walks
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CrystalGRW: Generative Modeling of Crystal Structures with Targeted Properties via Geodesic Random Walks Tangsongcharoen et al.: https://
arxiv.org/abs/2501.08998 #Artificialintelligence #DeepLearning #MachineLearning -
RAG-Driven Generative AI: Build Custom Retrieval Augmented Generation Pipelines
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RAG-Driven #GenerativeAI — Build custom Retrieval Augmented Generation pipelines: http://
amzn.to/3MWnIek v/ @PacktPublishing ——
#AI #MachineLearning #DataScience #GenAI #LLMs
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𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Implement RAG’s traceable outputs, linking each response to its source -
Deep Reinforcement Learning Hands-On Guide Third Edition
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Deep #ReinforcementLearning Hands-On — A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF: http://
amzn.to/3MV9o60 [Third Edition] v/ @PacktPublishing ——
#AI #MachineLearning #DeepLearning #DataScience #DataScientist
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𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼: