Papers with domain adaptation problem
PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains (2022.tacl-1)
Copied to clipboard
| Challenge: | Domain Adaptation (DA) algorithms suffer degradation when applied to out-of-distribution examples. |
| Approach: | They propose an example-based autoregressive Prompt learning algorithm for on-the-fly Any-Domain Adaptation . the algorithm is trained to generate a unique prompt that maps the test example to a semantic space . |
| Outcome: | The proposed model outperforms baselines in 14 multi-source adaptation scenarios. |
Projecting Embeddings for Domain Adaption: Joint Modeling of Sentiment Analysis in Diverse Domains (C18-1)
Copied to clipboard
| Challenge: | Existing domain adaptation methods for sentiment analysis are sensitive to domain differences, resulting in classifiers that perform poorly on new domains. |
| Approach: | They propose a domain adaptation problem as an embedding projection task using two mono-domain embeddable spaces and a bi-domain space to project across domains and predict sentiment. |
| Outcome: | The proposed model performs better on domains similar to state-of-the-art methods while requiring longer training times. |
WIND: Weighting Instances Differentially for Model-Agnostic Domain Adaptation (2021.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for instance weighting cannot learn the weights which make the model generalize well in target domain. |
| Approach: | They propose a modelagnostic instance weighting algorithm which can learn the instance weights instead of manually designed weighting metrics. |
| Outcome: | The proposed method can learn the instance weights instead of manually designed weighting metrics. |
Geometry-aware domain adaptation for unsupervised alignment of word embeddings (2020.acl-main)
Copied to clipboard
| Challenge: | Existing methods for learning bilingual word embeddings have been used in natural language processing. |
| Approach: | They propose a manifold based geometric approach for learning unsupervised alignment of word embeddings between the source and target languages. |
| Outcome: | The proposed approach outperforms state-of-the-art optimal transport based approach on bilingual lexicon induction task across several language pairs. |
Domain Adaptation for Person-Job Fit with Transferable Deep Global Match Network (D19-1)
Copied to clipboard
| Challenge: | Existing methods to solve person-job fit in single-domain setting are limited by labeled data. |
| Approach: | They propose a deep global match network for capturing the global semantic interactions between two sentences from a job posting and a candidate resume respectively. |
| Outcome: | The proposed model is effective when there is not enough labeled data. |