11 citations · 13 across the 3 of their papers we have counts for
3 papers
Mechanics of Next Token Prediction with Self-Attention
Yingcong Li, Yixiao Huang, M. Emrullah Ildiz +2
Transformer-based language models are trained on large datasets to predict the next token given an input sequence. Despite this simple training objective, they have led to revoluti…
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
M. Emrullah Ildiz, Yixiao Huang, Yingcong Li +2
Modern language models rely on the transformer architecture and attention mechanism to perform language understanding and text generation. In this work, we study learning a 1-layer…
Transformers as Algorithms: Generalization and Stability in In-context Learning
Yingcong Li, M. Emrullah Ildiz, Dimitris Papailiopoulos +1
In-context learning (ICL) is a type of prompting where a transformer model operates on a sequence of (input, output) examples and performs inference on-the-fly. In this work, we fo…