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Llama See, Llama Do: A Mechanistic Perspective on Contextual Entrainment and Distraction in LLMs
14 May 2025
Jingcheng Niu
Xingdi Yuan
Tong Wang
Hamidreza Saghir
Amir H. Abdi
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Papers citing
"Llama See, Llama Do: A Mechanistic Perspective on Contextual Entrainment and Distraction in LLMs"
10 / 10 papers shown
Title
Finding Transformer Circuits with Edge Pruning
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The Power of Noise: Redefining Retrieval for RAG Systems
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26 Jan 2024
Linearity of Relation Decoding in Transformer Language Models
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Yonatan Belinkov
David Bau
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17 Aug 2023
Tracr: Compiled Transformers as a Laboratory for Interpretability
David Lindner
János Kramár
Sebastian Farquhar
Matthew Rahtz
Tom McGrath
Vladimir Mikulik
117
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12 Jan 2023
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small
Kevin Wang
Alexandre Variengien
Arthur Conmy
Buck Shlegeris
Jacob Steinhardt
318
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01 Nov 2022
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
323
528
0
24 Sep 2022
Locating and Editing Factual Associations in GPT
Kevin Meng
David Bau
A. Andonian
Yonatan Belinkov
KELM
253
1,390
0
10 Feb 2022
Measuring and Improving Consistency in Pretrained Language Models
Yanai Elazar
Nora Kassner
Shauli Ravfogel
Abhilasha Ravichander
Eduard H. Hovy
Hinrich Schütze
Yoav Goldberg
HILM
331
370
0
01 Feb 2021
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
908
42,520
0
28 May 2020
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio
Nicholas Léonard
Aaron Courville
403
3,158
0
15 Aug 2013
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