Papers with neural re-ranker
Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations (2021.eacl-main)
Copied to clipboard
| Challenge: | Major scandals in corporate history have urged the need for regulatory compliance, where organizations need to ensure that their controls (processes) comply with relevant laws, regulations, and policies. |
| Approach: | They introduce regulatory information retrieval (REG-IR) an application of document-to-document information retrievals where the query is an entire document making the task more challenging than traditional IR where the queries are short. |
| Outcome: | The proposed approach is more challenging than traditional IR where the query is an entire document making the task more challenging. |
Incorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-Ranking (2022.emnlp-main)
Copied to clipboard
| Challenge: | Extensive experiments demonstrate that integrating relevance feedback directly into neural re-ranking models improves their performance. |
| Approach: | They propose a kNN approach that re-ranks documents based on their similarity with the query and the documents the user considers relevant. |
| Outcome: | The proposed approach outperforms all other methods by 5.2% on large-scale information retrieval datasets. |