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In-Context Learning Dynamics with Random Binary Sequences

In-Context Learning Dynamics with Random Binary Sequences

26 October 2023
Eric J. Bigelow
Ekdeep Singh Lubana
Robert P. Dick
Hidenori Tanaka
T. Ullman
ArXivPDFHTML

Papers citing "In-Context Learning Dynamics with Random Binary Sequences"

12 / 12 papers shown
Title
ICLR: In-Context Learning of Representations
ICLR: In-Context Learning of Representations
Core Francisco Park
Andrew Lee
Ekdeep Singh Lubana
Yongyi Yang
Maya Okawa
Kento Nishi
Martin Wattenberg
Hidenori Tanaka
AIFin
114
3
0
29 Dec 2024
How Language Model Hallucinations Can Snowball
How Language Model Hallucinations Can Snowball
Muru Zhang
Ofir Press
William Merrill
Alisa Liu
Noah A. Smith
HILM
LRM
78
252
0
22 May 2023
Finding Neurons in a Haystack: Case Studies with Sparse Probing
Finding Neurons in a Haystack: Case Studies with Sparse Probing
Wes Gurnee
Neel Nanda
Matthew Pauly
Katherine Harvey
Dmitrii Troitskii
Dimitris Bertsimas
MILM
153
186
0
02 May 2023
How does GPT-2 compute greater-than?: Interpreting mathematical
  abilities in a pre-trained language model
How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model
Michael Hanna
Ollie Liu
Alexandre Variengien
LRM
184
116
0
30 Apr 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
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of
  Chain-of-Thought
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
Abulhair Saparov
He He
ELM
LRM
ReLM
116
274
0
03 Oct 2022
Neural Networks and the Chomsky Hierarchy
Neural Networks and the Chomsky Hierarchy
Grégoire Delétang
Anian Ruoss
Jordi Grau-Moya
Tim Genewein
L. Wenliang
...
Chris Cundy
Marcus Hutter
Shane Legg
Joel Veness
Pedro A. Ortega
UQCV
94
129
0
05 Jul 2022
Using cognitive psychology to understand GPT-3
Using cognitive psychology to understand GPT-3
Marcel Binz
Eric Schulz
ELM
LLMAG
242
434
0
21 Jun 2022
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLM
LRM
291
4,048
0
24 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason W. Wei
Xuezhi Wang
Dale Schuurmans
Maarten Bosma
Brian Ichter
F. Xia
Ed H. Chi
Quoc Le
Denny Zhou
LM&Ro
LRM
AI4CE
ReLM
315
8,402
0
28 Jan 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming
  Few-Shot Prompt Order Sensitivity
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Yao Lu
Max Bartolo
Alastair Moore
Sebastian Riedel
Pontus Stenetorp
AILaw
LRM
277
1,114
0
18 Apr 2021
Probing Classifiers: Promises, Shortcomings, and Advances
Probing Classifiers: Promises, Shortcomings, and Advances
Yonatan Belinkov
221
402
0
24 Feb 2021
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