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1
A Quantitative and Qualitative Analysis of Schizophrenia Language ...
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2
Towards Responsible Natural Language Annotation for the Varieties of Arabic ...
Bergman, A. Stevie; Diab, Mona T.. - : arXiv, 2022
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3
Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation ...
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4
Few-shot Learning with Multilingual Language Models ...
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5
AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization ...
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6
Green NLP panel ...
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7
Detecting Hallucinated Content in Conditional Neural Sequence Generation ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.120 Abstract: Neural sequence models can generate highly fluent sentences, but recent studies have also shown that they are also prone to hallucinate additional content not supported by the input. This variety of fluent but wrong text is particularly problematic, as it will not be possible for users to tell they are being presented incorrect content. To detect these errors, we propose a task to predict whether each token in the output sequence is hallucinated (not contained in the input) and collect new manually annotated evaluation sets for this task. We also introduce a novel method for learning to model hallucination detection, using pretrained language models fine tuned on synthetic data that includes automatically inserted hallucinations. Experiments on machine translation and abstractive text summarization demonstrate the effectiveness of our proposed approach --- we consistently outperform strong baselines across all the 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/26211-detecting-hallucinated-content-in-conditional-neural-sequence-generation
https://dx.doi.org/10.48448/4s6r-5381
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8
Gender bias amplification during Speed-Quality optimization in Neural Machine Translation ...
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9
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ...
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10
Discrete Cosine Transform as Universal Sentence Encoder ...
Almarwani, Nada; Diab, Mona. - : arXiv, 2021
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11
Discrete Cosine Transform as Universal Sentence Encoder ...
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12
Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages ...
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13
DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking ...
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14
Mutlitask Learning for Cross-Lingual Transfer of Semantic Dependencies ...
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15
Overview for the Second Shared Task on Language Identification in Code-Switched Data ...
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16
WASA: A Web Application for Sequence Annotation ...
AlGhamdi, Fahad; Diab, Mona. - : arXiv, 2019
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17
Creating a Large Multi-Layered Representational Repository of Linguistic Code Switched Arabic Data ...
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18
Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues ...
Levi, Or; Hosseini, Pedram; Diab, Mona. - : arXiv, 2019
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19
Part of speech tagging for code switched data ...
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20
Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task ...
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