Papers with domain adaption
PIEKM: ML-based Procedural Information Extraction and Knowledge Management System for Materials Science Literature (2022.aacl-demo)
Copied to clipboard
| Challenge: | Existing literature search engines cannot deliver recipe steps of the literature . manual processing and assimilating useful information is expensive and time-consuming for researchers. |
| Approach: | They propose a machine learning-based procedural information extraction and knowledge management system that extracts procedural recipe steps, figures, and tables from materials science articles. |
| Outcome: | The proposed system extracts procedural information recipe steps, figures, and tables from materials science articles and provides information retrieval capability and statistics visualization functionality. |
Q-TOD: A Query-driven Task-oriented Dialogue System (2022.emnlp-main)
Copied to clipboard
| Challenge: | Existing pipelined task-oriented dialogue systems have difficulties adapting to unseen domains . end-to-end systems are plagued by large-scale knowledge bases in practice . |
| Approach: | They propose a query-driven task-oriented dialogue system that extracts dialogue context information into a natural language query. |
| Outcome: | The proposed system outperforms strong baselines and establishes a new state-of-the-art performance on three publicly available task-oriented dialogue datasets. |
Contextualized Semantic Distance between Highly Overlapped Texts (2023.findings-acl)
Copied to clipboard
| Challenge: | Conventional semantic metrics are based on word representations and are vulnerable to disturbance of overlapped components with similar representations. |
| Approach: | They propose a mask-and-predict strategy to evaluate the semantic distance between the overlapped sentences using words in the longest common sequence as neighboring words and use masked language modeling to predict their positions. |
| Outcome: | The proposed method outperforms the state-of-the-art in domain adaption by a huge margin. |
To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering (2023.acl-long)
Copied to clipboard
| Challenge: | Recent advances in open-domain question answering have demonstrated impressive accuracy on general-purpose domains like Wikipedia. |
| Approach: | They propose a more realistic end-to-end domain shift evaluation setting covering five diverse domains to assess model adaption. |
| Outcome: | The proposed model improves by 24 points when adapted to unsupervised datasets. |