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Learning Transformer Programs

Learning Transformer Programs

1 June 2023
Dan Friedman
Alexander Wettig
Danqi Chen
ArXivPDFHTML

Papers citing "Learning Transformer Programs"

8 / 8 papers shown
Title
Representing Rule-based Chatbots with Transformers
Representing Rule-based Chatbots with Transformers
Dan Friedman
Abhishek Panigrahi
Danqi Chen
59
1
0
15 Jul 2024
Finding Transformer Circuits with Edge Pruning
Finding Transformer Circuits with Edge Pruning
Adithya Bhaskar
Alexander Wettig
Dan Friedman
Danqi Chen
58
14
0
24 Jun 2024
Codebook Features: Sparse and Discrete Interpretability for Neural
  Networks
Codebook Features: Sparse and Discrete Interpretability for Neural Networks
Alex Tamkin
Mohammad Taufeeque
Noah D. Goodman
25
27
0
26 Oct 2023
Finding Alignments Between Interpretable Causal Variables and
  Distributed Neural Representations
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
Atticus Geiger
Zhengxuan Wu
Christopher Potts
Thomas F. Icard
Noah D. Goodman
CML
73
98
0
05 Mar 2023
Interpretability in the Wild: a Circuit for Indirect Object
  Identification in GPT-2 small
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small
Kevin Wang
Alexandre Variengien
Arthur Conmy
Buck Shlegeris
Jacob Steinhardt
210
491
0
01 Nov 2022
In-context Learning and Induction Heads
In-context Learning and Induction Heads
Catherine Olsson
Nelson Elhage
Neel Nanda
Nicholas Joseph
Nova Dassarma
...
Tom B. Brown
Jack Clark
Jared Kaplan
Sam McCandlish
C. Olah
240
456
0
24 Sep 2022
Train Short, Test Long: Attention with Linear Biases Enables Input
  Length Extrapolation
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
Ofir Press
Noah A. Smith
M. Lewis
245
695
0
27 Aug 2021
Probing Classifiers: Promises, Shortcomings, and Advances
Probing Classifiers: Promises, Shortcomings, and Advances
Yonatan Belinkov
224
404
0
24 Feb 2021
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