Papers with priming
Priming Ancient Korean Neural Machine Translation (2022.lrec-1)
Copied to clipboard
| Challenge: | Recent studies have focused on the restoration and translation of historical languages. |
| Approach: | They propose to use two different stimuli to priming ancient-Korean NMT . they confirm the possibility of developing a human-centric model based on cognitive science . |
| Outcome: | The proposed model can be used to translate historical Korean documents using neural machine translation. |
Dual Mechanism Priming Effects in Hindi Word Order (2022.aacl-main)
Copied to clipboard
| Challenge: | Existing studies have shown that word order choices can be primed by preceding sentences. |
| Approach: | They propose to model lexical priming and lexically-independent syntactic priming using a logistic regression model. |
| Outcome: | The proposed hypothesis supports multiple cognitive mechanisms . the experimental record shows that lexical priming and lexically-independent priming affect complementary sets of verb classes. |
Evaluating Approaches to Personalizing Language Models (2020.lrec-1)
Copied to clipboard
| Challenge: | a large amount of text is not available for training a user-specific language model, which suggests a need to personalize language models with only a small amount of data. |
| Approach: | They propose three approaches to personalize a language model that was trained on a large background corpus using a relatively small amount of text from an individual user. |
| Outcome: | The proposed techniques outperform language model adaptation based on demographic factors. |
Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Media (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Information manipulation campaigns rely on textbased news and social media content, and NLP can be a valuable tool in combating them. |
| Approach: | They propose to use a dataset to examine the use of NLP in public opinion manipulation campaigns in the 2022 Russia-Ukraine war. |
| Outcome: | The proposed dataset contains 38M+ posts from Russian media outlets on Twitter and VKontakte, as well as public activity and responses, immediately preceding and during the 2022 Russia-Ukraine war. |