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Birds have four legs?! NumerSense: Probing Numerical Commonsense
  Knowledge of Pre-trained Language Models
v1v2 (latest)

Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
2 May 2020
Bill Yuchen Lin
Seyeon Lee
Rahul Khanna
Xiang Ren
    AIMat
ArXiv (abs)PDFHTML

Papers citing "Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models"

50 / 109 papers shown
Beyond Plain Demos: A Demo-centric Anchoring Paradigm for In-Context Learning in Alzheimer's Disease Detection
Beyond Plain Demos: A Demo-centric Anchoring Paradigm for In-Context Learning in Alzheimer's Disease Detection
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Haoran Yin
Yongzhu Miao
Jintao Tang
Shasha Li
Ting Wang
133
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0
10 Nov 2025
Retrieval-Constrained Decoding Reveals Underestimated Parametric Knowledge in Language Models
Retrieval-Constrained Decoding Reveals Underestimated Parametric Knowledge in Language Models
Rajaa El Hamdani
Samy Haffoudhi
Nils Holzenberger
Fabian M. Suchanek
Thomas Bonald
Fragkiskos D. Malliaros
KELM
188
0
0
27 Sep 2025
Intermediate Languages Matter: Formal Languages and LLMs affect Neurosymbolic Reasoning
Intermediate Languages Matter: Formal Languages and LLMs affect Neurosymbolic ReasoningInternational Conference on Semantic Systems (i-Semantics), 2025
Alexander Beiser
David Penz
Nysret Musliu
LRM
211
0
0
04 Sep 2025
Is Large Language Model Performance on Reasoning Tasks Impacted by Different Ways Questions Are Asked?
Is Large Language Model Performance on Reasoning Tasks Impacted by Different Ways Questions Are Asked?Annual Meeting of the Association for Computational Linguistics (ACL), 2025
Seok Hwan Song
Mohna Chakraborty
Qi Li
Wallapak Tavanapong
ELMLRM
257
1
0
21 Jul 2025
WinoWhat: A Parallel Corpus of Paraphrased WinoGrande Sentences with Common Sense Categorization
WinoWhat: A Parallel Corpus of Paraphrased WinoGrande Sentences with Common Sense Categorization
I. Gevers
Victor De Marez
Luna De Bruyne
Walter Daelemans
392
2
0
31 Mar 2025
Commonsense Reasoning in Arab Culture
Commonsense Reasoning in Arab CultureAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Abdelrahman Boda Sadallah
Junior Cedric Tonga
Khalid Almubarak
Saeed Almheiri
Farah Atif
Chatrine Qwaider
Karima Kadaoui
Sara Shatnawi
Yaser Alesh
Fajri Koto
LRM
486
17
0
18 Feb 2025
Number Cookbook: Number Understanding of Language Models and How to Improve It
Number Cookbook: Number Understanding of Language Models and How to Improve ItInternational Conference on Learning Representations (ICLR), 2024
Haotong Yang
Yi Hu
Shijia Kang
Zhouchen Lin
Muhan Zhang
LRM
608
42
0
06 Nov 2024
The Factuality of Large Language Models in the Legal Domain
The Factuality of Large Language Models in the Legal DomainInternational Conference on Information and Knowledge Management (CIKM), 2024
Rajaa El Hamdani
Thomas Bonald
Fragkiskos D. Malliaros
Nils Holzenberger
Fabian M. Suchanek
AILawHILM
381
13
0
18 Sep 2024
Towards a Generative Approach for Emotion Detection and Reasoning
Towards a Generative Approach for Emotion Detection and Reasoning
Ankita Bhaumik
T. Strzalkowski
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259
5
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09 Aug 2024
Development of Cognitive Intelligence in Pre-trained Language Models
Development of Cognitive Intelligence in Pre-trained Language Models
Raj Sanjay Shah
Khushi Bhardwaj
Sashank Varma
481
3
0
01 Jul 2024
Paraphrase Types Elicit Prompt Engineering Capabilities
Paraphrase Types Elicit Prompt Engineering Capabilities
Jan Philip Wahle
Terry Ruas
Yang Xu
Bela Gipp
582
19
0
28 Jun 2024
RUPBench: Benchmarking Reasoning Under Perturbations for Robustness
  Evaluation in Large Language Models
RUPBench: Benchmarking Reasoning Under Perturbations for Robustness Evaluation in Large Language Models
Yuqing Wang
Yun Zhao
LRMAAMLELM
311
9
0
16 Jun 2024
Are LLMs classical or nonmonotonic reasoners? Lessons from generics
Are LLMs classical or nonmonotonic reasoners? Lessons from generics
Alina Leidinger
R. Rooij
Ekaterina Shutova
LRM
362
9
0
05 Jun 2024
NUMCoT: Numerals and Units of Measurement in Chain-of-Thought Reasoning
  using Large Language Models
NUMCoT: Numerals and Units of Measurement in Chain-of-Thought Reasoning using Large Language Models
Ancheng Xu
Minghuan Tan
Lei Wang
Min Yang
Ruifeng Xu
LRM
215
1
0
05 Jun 2024
Can Large Language Models put 2 and 2 together? Probing for Entailed
  Arithmetical Relationships
Can Large Language Models put 2 and 2 together? Probing for Entailed Arithmetical Relationships
D. Panas
S. Seth
V. Belle
ReLMLRM
269
6
0
30 Apr 2024
Exploring Internal Numeracy in Language Models: A Case Study on ALBERT
Exploring Internal Numeracy in Language Models: A Case Study on ALBERT
Ulme Wennberg
G. Henter
MILM
361
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25 Apr 2024
IndoCulture: Exploring Geographically-Influenced Cultural Commonsense
  Reasoning Across Eleven Indonesian Provinces
IndoCulture: Exploring Geographically-Influenced Cultural Commonsense Reasoning Across Eleven Indonesian ProvincesTransactions of the Association for Computational Linguistics (TACL), 2024
Fajri Koto
Rahmad Mahendra
Nurul Aisyah
Timothy Baldwin
LRM
407
43
0
02 Apr 2024
Rule or Story, Which is a Better Commonsense Expression for Talking with
  Large Language Models?
Rule or Story, Which is a Better Commonsense Expression for Talking with Large Language Models?
Ning Bian
Xianpei Han
Hongyu Lin
Yaojie Lu
Xianpei Han
Le Sun
326
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0
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EvoGrad: A Dynamic Take on the Winograd Schema Challenge with Human
  Adversaries
EvoGrad: A Dynamic Take on the Winograd Schema Challenge with Human Adversaries
Jing Han Sun
Ali Emami
396
6
0
20 Feb 2024
Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large
  Language Models
Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Spyridon Mouselinos
Henryk Michalewski
Mateusz Malinowski
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251
14
0
06 Feb 2024
Temporal Blind Spots in Large Language Models
Temporal Blind Spots in Large Language ModelsWeb Search and Data Mining (WSDM), 2024
Jonas Wallat
Adam Jatowt
Avishek Anand
447
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22 Jan 2024
In-context Learning with Retrieved Demonstrations for Language Models: A
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In-context Learning with Retrieved Demonstrations for Language Models: A Survey
an Luo
Xin Xu
Yue Liu
Panupong Pasupat
Mehran Kazemi
RALM
860
83
0
21 Jan 2024
Gemini in Reasoning: Unveiling Commonsense in Multimodal Large Language
  Models
Gemini in Reasoning: Unveiling Commonsense in Multimodal Large Language Models
Yuqing Wang
Yun Zhao
VLMReLMLRM
378
27
0
29 Dec 2023
Enhancing Quantitative Reasoning Skills of Large Language Models through
  Dimension Perception
Enhancing Quantitative Reasoning Skills of Large Language Models through Dimension PerceptionIEEE International Conference on Data Engineering (ICDE), 2023
Yuncheng Huang
Qi He
Jiaqing Liang
Sihang Jiang
Yanghua Xiao
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209
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29 Dec 2023
CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks
  for Chinese Large Language Models
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Dan Shi
Chaobin You
Jian-Tao Huang
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Deyi Xiong
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250
2
0
20 Dec 2023
Exploring the Numerical Reasoning Capabilities of Language Models: A
  Comprehensive Analysis on Tabular Data
Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular DataConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Mubashara Akhtar
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287
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ROME: Evaluating Pre-trained Vision-Language Models on Reasoning beyond
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Kankan Zhou
Eason Lai
Wei Bin Au Yeong
K. Mouratidis
Jing Jiang
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254
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CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks
CRoW: Benchmarking Commonsense Reasoning in Real-World TasksConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Mete Ismayilzada
Debjit Paul
Syrielle Montariol
Mor Geva
Antoine Bosselut
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342
8
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23 Oct 2023
GeoLLM: Extracting Geospatial Knowledge from Large Language Models
GeoLLM: Extracting Geospatial Knowledge from Large Language ModelsInternational Conference on Learning Representations (ICLR), 2023
Rohin Manvi
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Marshall Burke
David B. Lobell
Stefano Ermon
489
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Crystal: Introspective Reasoners Reinforced with Self-Feedback
Crystal: Introspective Reasoners Reinforced with Self-FeedbackConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Hamish Ivison
Ramakanth Pasunuru
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Asli Celikyilmaz
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297
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Can NLP Models Ídentify', 'Distinguish', and 'Justify' Questions that
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Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large
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The Web Can Be Your Oyster for Improving Large Language Models
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Human Behavioral Benchmarking: Numeric Magnitude Comparison Effects in
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