Papers with supervised learning paradigm
DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data (P18-4)
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| Challenge: | Existing methods to extract events from documents are limited due to the high cost of labeling . Experimental results demonstrate the effectiveness of a document-level Chinese financial event extraction system. |
| Approach: | They propose a document-level Chinese financial event extraction framework which detects event mentions and extracts events from financial news. |
| Outcome: | The proposed system detects event mentions and extracts events from financial news . it can generate large scale labeled data and extract events from entire document . |
Dialogue in the Wild: Learning from a Deployed Role-Playing Game with Humans and Bots (2021.findings-acl)
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| Challenge: | prevailing paradigm in natural language processing research is to build a fixed dataset and freeze it, without any ability for the model to interact with humans using language at training time at all. |
| Approach: | They build and deploy a role-playing game where players converse with learning agents situated in an open-domain fantasy world. |
| Outcome: | The proposed game enables human players to learn from human conversations and improves on their models. |
Variational Weakly Supervised Sentiment Analysis with Posterior Regularization (2021.eacl-main)
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| Challenge: | Existing methods for sentiment analysis require human annotations, but they are scarce. |
| Approach: | They propose a posterior regularization framework to control the posterior distribution of label assignment. |
| Outcome: | The proposed framework improves the variational approach to the weakly supervised sentiment analysis and the performance is more stable with smaller prediction variance. |