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Language Models Do Hard Arithmetic Tasks Easily and Hardly Do Easy
  Arithmetic Tasks

Language Models Do Hard Arithmetic Tasks Easily and Hardly Do Easy Arithmetic Tasks

4 June 2024
Andrew Gambardella
Yusuke Iwasawa
Yutaka Matsuo
    LRM
ArXivPDFHTML

Papers citing "Language Models Do Hard Arithmetic Tasks Easily and Hardly Do Easy Arithmetic Tasks"

8 / 8 papers shown
Title
A Minimum Description Length Approach to Regularization in Neural Networks
A Minimum Description Length Approach to Regularization in Neural Networks
Matan Abudy
Orr Well
Emmanuel Chemla
Roni Katzir
Nur Lan
17
0
0
19 May 2025
AGI Is Coming... Right After AI Learns to Play Wordle
AGI Is Coming... Right After AI Learns to Play Wordle
Sarath Shekkizhar
Romain Cosentino
LLMAG
52
0
0
21 Apr 2025
Process or Result? Manipulated Ending Tokens Can Mislead Reasoning LLMs to Ignore the Correct Reasoning Steps
Process or Result? Manipulated Ending Tokens Can Mislead Reasoning LLMs to Ignore the Correct Reasoning Steps
Yu Cui
Bryan Hooi
Yujun Cai
Yiwei Wang
LRM
42
3
0
25 Mar 2025
The Lookahead Limitation: Why Multi-Operand Addition is Hard for LLMs
The Lookahead Limitation: Why Multi-Operand Addition is Hard for LLMs
Tanja Baeumel
Josef van Genabith
Simon Ostermann
LRM
67
1
0
27 Feb 2025
Grandes modelos de lenguaje: de la predicción de palabras a la comprensión?
Grandes modelos de lenguaje: de la predicción de palabras a la comprensión?
Carlos Gómez-Rodríguez
SyDa
AILaw
ELM
VLM
115
0
0
25 Feb 2025
In-Context Learning May Not Elicit Trustworthy Reasoning: A-Not-B Errors
  in Pretrained Language Models
In-Context Learning May Not Elicit Trustworthy Reasoning: A-Not-B Errors in Pretrained Language Models
Pengrui Han
Peiyang Song
Haofei Yu
Jiaxuan You
ReLM
LRM
41
1
0
23 Sep 2024
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
331
4,077
0
24 May 2022
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,167
0
06 Jun 2015
1