Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning

9 September 2021

Papers citing "Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning"

50 / 51 papers shown

Title
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence Tal Schuster Adam Fisch Regina Barzilay 77 234 0 15 Mar 2021
How Many Data Points is a Prompt Worth? Teven Le Scao Alexander M. Rush VLM 145 302 0 15 Mar 2021
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU Models Mengnan Du Varun Manjunatha R. Jain Ruchi Deshpande Franck Dernoncourt Jiuxiang Gu Tong Sun Xia Hu 85 108 0 11 Mar 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 375 1,966 0 31 Dec 2020
Learning from others' mistakes: Avoiding dataset biases without modeling them Victor Sanh Thomas Wolf Yonatan Belinkov Alexander M. Rush 52 116 0 02 Dec 2020
Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles Christopher Clark Mark Yatskar Luke Zettlemoyer 57 62 0 07 Nov 2020
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification Timo Schick Helmut Schmid Hinrich Schütze VLM 75 208 0 26 Oct 2020
Improving Robustness by Augmenting Training Sentences with Predicate-Argument Structures N. Moosavi M. Boer Prasetya Ajie Utama Iryna Gurevych 59 13 0 23 Oct 2020
Characterising Bias in Compressed Models Sara Hooker Nyalleng Moorosi Gregory Clark Samy Bengio Emily L. Denton 64 185 0 06 Oct 2020
Towards Debiasing NLU Models from Unknown Biases Prasetya Ajie Utama N. Moosavi Iryna Gurevych 57 155 0 25 Sep 2020
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners Timo Schick Hinrich Schütze 117 972 0 15 Sep 2020
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines Marius Mosbach Maksym Andriushchenko Dietrich Klakow 158 357 0 08 Jun 2020
Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance Prasetya Ajie Utama N. Moosavi Iryna Gurevych OODD 114 127 0 01 May 2020
Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting Sanyuan Chen Yutai Hou Yiming Cui Wanxiang Che Ting Liu Xiangzhan Yu KELM CLL 97 224 0 27 Apr 2020
Syntactic Data Augmentation Increases Robustness to Inference Heuristics Junghyun Min R. Thomas McCoy Dipanjan Das Emily Pitler Tal Linzen 70 179 0 24 Apr 2020
Don't Stop Pretraining: Adapt Language Models to Domains and Tasks Suchin Gururangan Ana Marasović Swabha Swayamdipta Kyle Lo Iz Beltagy Doug Downey Noah A. Smith VLM AI4CE CLL 152 2,423 0 23 Apr 2020
The Right Tool for the Job: Matching Model and Instance Complexities Roy Schwartz Gabriel Stanovsky Swabha Swayamdipta Jesse Dodge Noah A. Smith 93 169 0 16 Apr 2020
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping Jesse Dodge Gabriel Ilharco Roy Schwartz Ali Farhadi Hannaneh Hajishirzi Noah A. Smith 95 595 0 15 Feb 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 341 1,613 0 21 Jan 2020
Adversarial NLI: A New Benchmark for Natural Language Understanding Yixin Nie Adina Williams Emily Dinan Joey Tianyi Zhou Jason Weston Douwe Kiela 118 1,005 0 31 Oct 2019
Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets Ohad Rozen Vered Shwartz Roee Aharoni Ido Dagan AAML 72 38 0 21 Oct 2019
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter Victor Sanh Lysandre Debut Julien Chaumond Thomas Wolf 230 7,498 0 02 Oct 2019
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data Divyansh Kaushik Eduard H. Hovy Zachary Chase Lipton CML 86 569 0 26 Sep 2019
End-to-End Bias Mitigation by Modelling Biases in Corpora Rabeeh Karimi Mahabadi Yonatan Belinkov James Henderson 117 180 0 13 Sep 2019
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual He He Sheng Zha Haohan Wang 60 199 0 28 Aug 2019
Towards Debiasing Fact Verification Models Tal Schuster Darsh J. Shah Yun Jie Serene Yeo Daniel Filizzola Enrico Santus Regina Barzilay 87 211 0 14 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 612 24,431 0 26 Jul 2019
Green AI Roy Schwartz Jesse Dodge Noah A. Smith Oren Etzioni 102 1,144 0 22 Jul 2019
Probing Neural Network Comprehension of Natural Language Arguments Timothy Niven Hung-Yu kao AAML 85 454 0 17 Jul 2019
HellaSwag: Can a Machine Really Finish Your Sentence? Rowan Zellers Ari Holtzman Yonatan Bisk Ali Farhadi Yejin Choi 168 2,468 0 19 May 2019
BERT Rediscovers the Classical NLP Pipeline Ian Tenney Dipanjan Das Ellie Pavlick MILM SSeg 133 1,471 0 15 May 2019
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets Nelson F. Liu Roy Schwartz Noah A. Smith AAML 68 106 0 04 Apr 2019
PAWS: Paraphrase Adversaries from Word Scrambling Yuan Zhang Jason Baldridge Luheng He 71 543 0 01 Apr 2019
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference R. Thomas McCoy Ellie Pavlick Tal Linzen 129 1,237 0 04 Feb 2019
Analyzing Compositionality-Sensitivity of NLI Models Yixin Nie Yicheng Wang Joey Tianyi Zhou CoGe 52 82 0 16 Nov 2018
How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks Divyansh Kaushik Zachary Chase Lipton ELM 69 232 0 14 Aug 2018
Stress Test Evaluation for Natural Language Inference Aakanksha Naik Abhilasha Ravichander Norman M. Sadeh Carolyn Rose Graham Neubig ELM 67 376 0 02 Jun 2018
Breaking NLI Systems with Sentences that Require Simple Lexical Inferences Max Glockner Vered Shwartz Yoav Goldberg NAI 72 366 0 06 May 2018
Hypothesis Only Baselines in Natural Language Inference Adam Poliak Jason Naradowsky Aparajita Haldar Rachel Rudinger Benjamin Van Durme 229 579 0 02 May 2018
Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment Masatoshi Tsuchiya 56 160 0 22 Apr 2018
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 1.1K 7,154 0 20 Apr 2018
Evaluating Compositionality in Sentence Embeddings Ishita Dasgupta Demi Guo Andreas Stuhlmuller S. Gershman Noah D. Goodman CoGe 61 121 0 12 Feb 2018
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference Benoit Jacob S. Kligys Bo Chen Menglong Zhu Matthew Tang Andrew G. Howard Hartwig Adam Dmitry Kalenichenko MQ 150 3,123 0 15 Dec 2017
Adversarial Examples for Evaluating Reading Comprehension Systems Robin Jia Percy Liang AAML ELM 196 1,605 0 23 Jul 2017
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference Adina Williams Nikita Nangia Samuel R. Bowman 517 4,476 0 18 Apr 2017
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task Roy Schwartz Maarten Sap Ioannis Konstas Leila Zilles Yejin Choi Noah A. Smith 76 120 0 07 Feb 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 354 7,504 0 02 Dec 2016
A large annotated corpus for learning natural language inference Samuel R. Bowman Gabor Angeli Christopher Potts Christopher D. Manning 307 4,282 0 21 Aug 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 310 6,672 0 08 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 344 19,634 0 09 Mar 2015