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FIM: Filling in the Middle for Language Models
This 2022 academic paper explores Fill-in-the-Middle (FIM) capabilities in causal decoder-based language models, demonstrating that these models can learn to infill text effectively by simply…
BPE: Subword Units for Neural Machine Translation of Rare Words
This 2016 academic paper addresses the challenge of translating rare and unknown words in Neural Machine Translation (NMT), a common issue as NMT models typically operate with a fixed vocabulary…
Distributed Word and Phrase Representations
This 2013 paper introduces advancements to the continuous Skip-gram model, a method for learning high-quality distributed vector representations of words. The authors present extensions like…
Efficient Word Vectors for Large Datasets
This 2013 academic paper introduces two new model architectures, Continuous Bag-of-Words (CBOW) and Skip-gram, designed for efficiently computing continuous vector representations of words from vast…
A Neural Probabilistic Language Model
This paper published in 2003 introduces a neural probabilistic language model designed to address the curse of dimensionality inherent in modeling word sequences. The authors propose learning a…
Softmax: Neural Networks and Maximum Mutual Information Estimation
The paper published in 1989, "Training Stochastic Model Recognition Algorithms as Networks can lead to Maximum Mutual Information Estimation of Parameters" by John S. Bridle, proposes a novel…
Back-Propagating Errors for Visual and Stereo Recognition
The paper on backpropagation was published in 1986.The paper presents a collaborative research effort focusing on back-propagation as a method for learning representations within neural networks. One…
The Parallel Distributed Processing Perspective
This paper published in 1986 introduces the concept of Parallel Distributed Processing (PDP) models, offering a new perspective on how human cognition works, contrasting it with traditional…
The Perceptron: A Theory of Statistical Separability
The 1958 paper on Perceptrons, by Marvin L. Minsky and Seymour A. Papert, offers an expanded edition exploring artificial intelligence, particularly pattern recognition, and learning through linear…
A Logical Calculus of Ideas Immanent in Nervous Activity
Perhaps the first related papers influencing the rise of the design of neural networks, published in 1943! The paper, "A Logical Calculus of the Ideas Immanent in Nervous Activity," is a foundational…
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AI: Origins has published 10 episodes since August 2025, covering topics in Technology.
AI: Origins is currently dormant with new episodes hourly. Average episode length is 16m.
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