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Data Similarity is Not Enough to Explain Language Model Performance

Data Similarity is Not Enough to Explain Language Model Performance

15 November 2023
Gregory Yauney
Emily Reif
David M. Mimno
ArXivPDFHTML

Papers citing "Data Similarity is Not Enough to Explain Language Model Performance"

10 / 10 papers shown
Title
Interrogating LLM design under a fair learning doctrine
Interrogating LLM design under a fair learning doctrine
Johnny Tian-Zheng Wei
Maggie Wang
Ameya Godbole
Jonathan H. Choi
Robin Jia
27
0
0
22 Feb 2025
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models
Yulei Qin
Yuncheng Yang
Pengcheng Guo
Gang Li
Hang Shao
Yuchen Shi
Zihan Xu
Yun Gu
Ke Li
Xing Sun
ALM
88
11
0
31 Dec 2024
LMD3: Language Model Data Density Dependence
LMD3: Language Model Data Density Dependence
John Kirchenbauer
Garrett Honke
Gowthami Somepalli
Jonas Geiping
Daphne Ippolito
Katherine Lee
Tom Goldstein
David Andre
27
6
0
10 May 2024
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency
  Determines Multimodal Model Performance
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
Vishaal Udandarao
Ameya Prabhu
Adhiraj Ghosh
Yash Sharma
Philip H. S. Torr
Adel Bibi
Samuel Albanie
Matthias Bethge
VLM
118
43
0
04 Apr 2024
Out-of-Distribution Detection and Selective Generation for Conditional
  Language Models
Out-of-Distribution Detection and Selective Generation for Conditional Language Models
Jie Jessie Ren
Jiaming Luo
Yao-Min Zhao
Kundan Krishna
Mohammad Saleh
Balaji Lakshminarayanan
Peter J. Liu
OODD
64
92
0
30 Sep 2022
Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information
Understanding Dataset Difficulty with V\mathcal{V}V-Usable Information
Kawin Ethayarajh
Yejin Choi
Swabha Swayamdipta
154
157
0
16 Oct 2021
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
237
588
0
14 Jul 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Leo Gao
Stella Biderman
Sid Black
Laurence Golding
Travis Hoppe
...
Horace He
Anish Thite
Noa Nabeshima
Shawn Presser
Connor Leahy
AIMat
245
1,977
0
31 Dec 2020
With Little Power Comes Great Responsibility
With Little Power Comes Great Responsibility
Dallas Card
Peter Henderson
Urvashi Khandelwal
Robin Jia
Kyle Mahowald
Dan Jurafsky
225
115
0
13 Oct 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
294
6,927
0
20 Apr 2018
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