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Ara-Women-Hate: The first Arabic Hate Speech corpus regarding Women ...
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Towards the Early Detection of Child Predators in Chat Rooms: A BERT-based Approach ...
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3
STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.683/ Abstract: Sentence order prediction is the task of finding the correct order of sentences in a randomly ordered document. Correctly ordering the sentences requires an understanding of coherence with respect to the chronological sequence of events described in the text. Document-level contextual understanding and commonsense knowledge centered around these events are often essential in uncovering this coherence and predicting the exact chronological order. In this paper, we introduce STaCK—a framework based on graph neural networks and temporal commonsense knowledge to model global information and predict the relative order of sentences. Our graph network accumulates temporal evidence using knowledge of past and future and formulates sentence ordering as a constrained edge classification problem. We report results on five different datasets, and empirically show that the proposed method is naturally suitable for order prediction. The ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing; Neural Network
URL: https://underline.io/lecture/37588-stack-sentence-ordering-with-temporal-commonsense-knowledge
https://dx.doi.org/10.48448/z4ap-sf78
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4
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution ...
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5
Graphine: A Dataset for Graph-aware Terminology Definition Generation ...
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6
End-to-end style-conditioned poetry generation: What does it take to learn from examples alone? ...
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7
To what extent do human explanations of model behavior align with actual model behavior? ...
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8
Time-aware Graph Neural Network for Entity Alignment between Temporal Knowledge Graphs ...
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9
What’s Hidden in a One-layer Randomly Weighted Transformer? ...
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10
Finetuning Pretrained Transformers into RNNs ...
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11
Sometimes We Want Ungrammatical Translations ...
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12
Pruning Neural Machine Translation for Speed Using Group Lasso ...
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13
Elementary-Level Math Word Problem Generation using Pre-Trained Transformers ...
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14
Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings ...
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15
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation ...
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16
Knowledge Graph Representation Learning using Ordinary Differential Equations ...
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17
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations ...
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18
Mind the Context: The Impact of Contextualization in Neural Module Networks for Grounding Visual Referring Expressions ...
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19
EM ALBERT: a step towards equipping Manipuri for NLP ...
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20
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection ...
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