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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (1.029)
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Hits 41 – 60 of 1.029
41
KOAS: Korean Text Offensiveness Analysis System ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Park, SanHee
. - : Underline Science Inc., 2021
BASE
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42
Contrastive Code Representation Learning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Jain, Ajay
;
Jain, Paras
. - : Underline Science Inc., 2021
BASE
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43
Does Putting a Linguist in the Loop Improve NLU Data Collection ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Parrish, Alicia
. - : Underline Science Inc., 2021
BASE
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44
What are we learning from language? ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Lupyan, Gary
. - : Underline Science Inc., 2021
BASE
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45
Machine Translation Decoding beyond Beam Search ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Alayrac, Jean-Baptiste
;
Antonoglou, Ioannis
. - : Underline Science Inc., 2021
BASE
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46
Say `YES' to Positivity: Detecting Toxic Language in Workplace Communications ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Awadallah, Ahmed
;
Bennett, Paul
. - : Underline Science Inc., 2021
BASE
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47
Unsupervised Multi-View Post-OCR Error Correction With Language Models ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Brenner, Eliot
;
Broscheit, Samuel
. - : Underline Science Inc., 2021
BASE
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48
AttentionRank: Unsupervised Keyphrase Extraction using Self and Cross Attentions ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Ding, Haoran
;
Luo, Xiao
. - : Underline Science Inc., 2021
BASE
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49
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Vlado
;
Fang, Meng
. - : Underline Science Inc., 2021
BASE
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50
Multi-granularity Textual Adversarial Attack with Behavior Cloning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Chen, Yangyi
;
su, jin
. - : Underline Science Inc., 2021
BASE
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51
Automatic Fact-Checking with Document-level Annotations using BERT and Multiple Instance Learning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Park, Joonsuk
;
Sathe, Aalok
. - : Underline Science Inc., 2021
BASE
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52
Towards the Early Detection of Child Predators in Chat Rooms: A BERT-based Approach ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Kumbale, Sinchana
;
Singh, Smriti
. - : Underline Science Inc., 2021
BASE
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53
TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Iryna
;
Reimers, Nils
. - : Underline Science Inc., 2021
BASE
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54
WebSRC: A Dataset for Web-Based Structural Reading Comprehension ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Chen, Xingyu
. - : Underline Science Inc., 2021
BASE
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55
Improving Math Word Problems with Pre-trained Knowledge and Hierarchical Reasoning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Wen, Yingpeng
;
Xiao, Nong
. - : Underline Science Inc., 2021
BASE
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56
Semantic Categorization of Social Knowledge for Commonsense Question Answering ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Wang, Gengyu
. - : Underline Science Inc., 2021
BASE
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57
Adversarial Examples for Evaluating Math Word Problem Solvers ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Kumar, Vivek
;
Maheshwary, Rishabh
;
Pudi, Vikram
. - : Underline Science Inc., 2021
Abstract:
Standard accuracy metrics have shown that Math Word Problem (MWP) solvers have achieved high performance on benchmark datasets. However, the extent to which existing MWP solvers truly understand language and its relation with numbers is still unclear. In this paper, we generate adversarial attacks to evaluate the robustness of state-of-the-art MWP solvers. We propose two methods, Question Reordering and Sentence Paraphrasing to generate adversarial attacks. We conduct experiments across three neural MWP solvers over two benchmark datasets. On average, our attack method is able to reduce the accuracy of MWP solvers by over 40% on these datasets. Our results demonstrate that existing MWP solvers are sensitive to linguistic variations in the problem text. We verify the validity and quality of generated adversarial examples through human evaluation. ...
URL:
https://underline.io/lecture/38384-adversarial-examples-for-evaluating-math-word-problem-solvers
https://dx.doi.org/10.48448/xcn3-2415
BASE
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58
Pre-train or Annotate? Domain Adaptation with a Constrained Budget ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Bai, Fan
;
Ritter, Alan
. - : Underline Science Inc., 2021
BASE
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59
Corpus-based Open-Domain Event Type Induction ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Shen, Jiaming
. - : Underline Science Inc., 2021
BASE
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60
Learning with Different Amounts of Annotation: From Zero to Many Labels ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Eunsol
;
Gong, Chengyue
. - : Underline Science Inc., 2021
BASE
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