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In-context Learning and Induction Heads

In-context Learning and Induction Heads

24 September 2022
Catherine Olsson
Nelson Elhage
Neel Nanda
Nicholas Joseph
Nova Dassarma
T. Henighan
Benjamin Mann
Amanda Askell
Yuntao Bai
Anna Chen
Tom Conerly
Dawn Drain
Deep Ganguli
Zac Hatfield-Dodds
Danny Hernandez
Scott Johnston
Andy Jones
John Kernion
Liane Lovitt
Kamal Ndousse
Dario Amodei
Tom B. Brown
Jack Clark
Jared Kaplan
Sam McCandlish
C. Olah
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Papers citing "In-context Learning and Induction Heads"

6 / 6 papers shown
Title
On the generalization of language models from in-context learning and finetuning: a controlled study
On the generalization of language models from in-context learning and finetuning: a controlled study
Andrew Kyle Lampinen
Arslan Chaudhry
Stephanie Chan
Cody Wild
Diane Wan
Alex Ku
Jorg Bornschein
Razvan Pascanu
Murray Shanahan
James L. McClelland
26
57
0
01 May 2025
Studying Small Language Models with Susceptibilities
Studying Small Language Models with Susceptibilities
Garrett Baker
George Wang
Jesse Hoogland
Daniel Murfet
AAML
63
29
0
25 Apr 2025
Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism
Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism
Aviv Bick
Eric P. Xing
Albert Gu
RALM
57
49
0
22 Apr 2025
Bigram Subnetworks: Mapping to Next Tokens in Transformer Language Models
Bigram Subnetworks: Mapping to Next Tokens in Transformer Language Models
Tyler A. Chang
Benjamin Bergen
28
40
0
21 Apr 2025
Toward Understanding In-context vs. In-weight Learning
Toward Understanding In-context vs. In-weight Learning
Bryan Chan
Xinyi Chen
András Gyorgy
Dale Schuurmans
26
40
0
30 Oct 2024
Making Pre-trained Language Models Better Few-shot Learners
Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao
Adam Fisch
Danqi Chen
225
1,593
0
31 Dec 2020
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