The Foundations of LLMs, 1943-2026: A Curated Collection of Seminal Papers (github.com)

A new curated collection titled "The Foundations of LLMs, 1943-2026" has been announced, compiling seminal papers that chart the evolution of large language models (LLMs) from the early days of neural networks to the latest advancements in AI reasoning systems. Spanning over eight decades, the book features critical contributions organized chronologically across several pivotal stages, including foundational neural learning (1943-1990), the rise of sequence models and embeddings (1997-2013), the deep learning revolution (2012-2019), and the transformative impact of the transformer architecture (2016-2020). The collection serves not just as a historic archive but as a vital resource for understanding the key breakthroughs that have shaped current AI technologies. This anthology is significant for the AI/ML community as it provides a structured overview of the technical advancements foundational to modern LLMs, enabling researchers and practitioners to grasp the intellectual lineage behind contemporary models like GPT-4 and Llama. It emphasizes groundbreaking techniques and insights while adhering to strict criteria for inclusion, ensuring that each paper marks a genuine leap forward rather than an incremental step. By fostering a deeper appreciation of the evolution of AI, this compilation could inspire further innovations and collaborations in the field.