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Persian Sentence-level Sentiment Polarity Classification
In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03258138 ; ICOTEN, Jun 2021, Glasgow, United Kingdom (2021)
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2
Persian Sentence-level Sentiment Polarity Classification
In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03241928 ; ICOTEN, May 2021, Glasgow, France (2021)
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3
On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu ...
Mehmood, Khawar. - : UNSW Sydney, 2021
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4
Contextualised sentiment analysis in the financial domain
Daudert, Tobias. - : NUI Galway, 2021
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5
Developing Conversational Data and Detection of Conversational Humor in Telugu ...
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6
Detecting Gender Bias using Explainability ...
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7
Characterizing Test Anxiety on Social Media ...
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8
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ...
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9
Open Aspect Target Sentiment Classification with Natural Language Prompts ...
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10
SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis ...
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11
Connecting Attributions and QA Model Behavior on Realistic Counterfactuals ...
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12
End-to-end style-conditioned poetry generation: What does it take to learn from examples alone? ...
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13
Solving Aspect Category Sentiment Analysis as a Text Generation Task ...
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14
CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks ...
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15
Improving Multimodal fusion via Mutual Dependency Maximisation ...
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16
Perceived and Intended Sarcasm Detection with Graph Attention Networks ...
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17
Does Commonsense help in detecting Sarcasm? ...
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18
Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.321/ Abstract: Aspect-based sentiment analysis (ABSA) predicts the sentiment polarity towards a particular aspect term in an input sentence, which is significantly important in real-world applications. To perform ABSA, one faces a long-standing challenge that ABSA requires the model to have a good understanding of the contextual information, especially the particular patterns that suggests the sentiment polarity. However, these patterns vary in different sentences, especially when the sentences come from different sources (domains). Although leveraging extra labeled data from different sources (domains) is always a promising solution to address the challenge, in practical applications, these labeled data are always stored at different locations and might be inaccessible to each other due to privacy or legal concerns (e.g., the data are owned by different companies). To address the issue and benefit from extra labeled data, we propose a novel ABSA ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Sentiment Analysis
URL: https://underline.io/lecture/38051-improving-federated-learning-for-aspect-based-sentiment-analysis-via-topic-memories
https://dx.doi.org/10.48448/mdr3-y242
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19
How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI ...
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20
LMSOC: An Approach for Socially Sensitive Pretraining ...
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