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On the Limitations of Compute Thresholds as a Governance Strategy

On the Limitations of Compute Thresholds as a Governance Strategy

8 July 2024
Sara Hooker
ArXivPDFHTML

Papers citing "On the Limitations of Compute Thresholds as a Governance Strategy"

12 / 12 papers shown
Title
Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation
Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation
Maria Eriksson
Erasmo Purificato
Arman Noroozian
Joao Vinagre
Guillaume Chaslot
Emilia Gomez
David Fernandez Llorca
ELM
139
1
0
10 Feb 2025
MEG: Medical Knowledge-Augmented Large Language Models for Question Answering
MEG: Medical Knowledge-Augmented Large Language Models for Question Answering
Laura Cabello
Carmen Martin-Turrero
Uchenna Akujuobi
Anders Søgaard
Carlos Bobed
AI4MH
154
1
0
06 Nov 2024
RLHF Can Speak Many Languages: Unlocking Multilingual Preference
  Optimization for LLMs
RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs
John Dang
Arash Ahmadian
Kelly Marchisio
Julia Kreutzer
Ahmet Üstün
Sara Hooker
42
23
0
02 Jul 2024
LLM See, LLM Do: Guiding Data Generation to Target Non-Differentiable
  Objectives
LLM See, LLM Do: Guiding Data Generation to Target Non-Differentiable Objectives
Luísa Shimabucoro
Sebastian Ruder
Julia Kreutzer
Marzieh Fadaee
Sara Hooker
SyDa
36
4
0
01 Jul 2024
LLM Agents can Autonomously Exploit One-day Vulnerabilities
LLM Agents can Autonomously Exploit One-day Vulnerabilities
Richard Fang
R. Bindu
Akul Gupta
Daniel Kang
SILM
LLMAG
78
56
0
11 Apr 2024
Aya Dataset: An Open-Access Collection for Multilingual Instruction
  Tuning
Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning
Shivalika Singh
Freddie Vargus
Daniel D'souza
Börje F. Karlsson
Abinaya Mahendiran
...
Max Bartolo
Julia Kreutzer
Ahmet Üstün
Marzieh Fadaee
Sara Hooker
122
118
0
09 Feb 2024
Distilling Step-by-Step! Outperforming Larger Language Models with Less
  Training Data and Smaller Model Sizes
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Lokesh Nagalapatti
Chun-Liang Li
Chih-Kuan Yeh
Hootan Nakhost
Yasuhisa Fujii
Alexander Ratner
Ranjay Krishna
Chen-Yu Lee
Tomas Pfister
ALM
220
502
0
03 May 2023
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang
Jason W. Wei
Dale Schuurmans
Quoc Le
Ed H. Chi
Sharan Narang
Aakanksha Chowdhery
Denny Zhou
ReLM
BDL
LRM
AI4CE
314
3,273
0
21 Mar 2022
Estimating Example Difficulty Using Variance of Gradients
Estimating Example Difficulty Using Variance of Gradients
Chirag Agarwal
Daniel D'souza
Sara Hooker
210
107
0
26 Aug 2020
Measuring the Algorithmic Efficiency of Neural Networks
Measuring the Algorithmic Efficiency of Neural Networks
Danny Hernandez
Tom B. Brown
241
94
0
08 May 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
264
4,489
0
23 Jan 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
297
6,959
0
20 Apr 2018
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