Papers by Hadeel Saadany
Automatic Linking of Judgements to UK Supreme Court Hearings (2023.emnlp-industry)
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| Challenge: | a number of legal documents are archived in the UK, including the Supreme Court's decisions and video recordings of court hearings. |
| Approach: | They propose to link segments in the text judgement to semantically relevant timespans in the videos of the hearings. |
| Outcome: | The proposed tool links segments in the text judgement to semantically relevant timespans in the videos of the hearings. |
PLOD: An Abbreviation Detection Dataset for Scientific Documents (2022.lrec-1)
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| Challenge: | Existing datasets for abbreviation detection and extraction are limited. |
| Approach: | They propose to use a large-scale dataset for abbreviation detection and extraction that contains 160k+ segments automatically annotated with abbrevian and long forms. |
| Outcome: | The proposed dataset has an F1 score of 0.92 for abbreviations and 0.89 for detecting their corresponding long forms. |
Linking Judgement Text to Court Hearing Videos: UK Supreme Court as a Case Study (2024.lrec-main)
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| Challenge: | Typically, transcripts of legal hearings are lengthy, making it time-consuming for legal professionals to analyse crucial arguments. |
| Approach: | They propose to use judgement-hearing pairs to link sections of written judgements with relevant moments in Supreme Court hearing videos to improve access to justice. |
| Outcome: | The proposed tool connects sections of written judgements with relevant moments in Supreme Court hearing videos, streamlining access to critical information. |
Centrality-aware Product Retrieval and Ranking (2024.emnlp-industry)
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| Challenge: | Ambiguity and complexity of user queries often lead to mismatch between user’s intent and retrieved product titles or documents. |
| Approach: | They propose a user-intent centrality optimization approach which optimizes for the user intent in semantic product search. |
| Outcome: | The proposed approach improves product ranking efficiency for ambiguous queries and lexical terms with alphanumeric characters. |