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Hits 61 – 80 of 1.251

61
AND does not mean OR: Using Formal Languages to Study Language Models’ Representations ...
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62
Constructing Multi-Modal Dialogue Dataset by Replacing Text with Semantically Relevant Images ...
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63
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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64
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search ...
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65
DALC: the Dutch Abusive Language Corpus ...
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66
Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognition ...
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67
VL-BERT+: Detecting Protected Groups in Hateful Multimodal Memes ...
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68
Attention-based Contextual Language Model Adaptation for Speech Recognition ...
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69
Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech ...
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70
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning ...
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71
LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification ...
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72
Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions ...
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73
Evidence-based Factual Error Correction ...
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74
SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images ...
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75
A DQN-based Approach to Finding Precise Evidences for Fact Verification ...
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76
Embedding Time Differences in Context-sensitive Neural Networks for Learning Time to Event ...
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77
A Span-based Dynamic Local Attention Model for Sequential Sentence Classification ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-short.26 Abstract: Sequential sentence classification aims to classify each sentence in the document based on the context in which sentences appear. Most existing work addresses this problem using a hierarchical sequence labeling network. However, they ignore considering the latent segment structure of the document, in which contiguous sentences often have coherent semantics. In this paper, we proposed a span-based dynamic local attention model that could explicitly capture the structural information by the proposed supervised dynamic local attention. We further introduce an auxiliary task called span-based classification to explore the span-level representations. Extensive experiments show that our model achieves better or competitive performance against state-of-the-art baselines on two benchmark datasets. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25980-a-span-based-dynamic-local-attention-model-for-sequential-sentence-classification
https://dx.doi.org/10.48448/xhw7-c647
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78
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection ...
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79
2A: Sentiment Analysis, Stylistic Analysis, and Argument Mining #1 ...
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80
On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation ...
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