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TEAM KBC

Project title: Knowledge Based Case Retrieval

📁 Dataset Statistics

Split Queries Candidates
Train 1,678 5,452
Test 400 1,759

📈 Results Overview

Comparison of Micro-Averaged Metrics across Different Inference Settings

Setting Inf. Prec Rec F1
Full cases 1 0.3030 0.3127 0.3078
2 0.3272 0.2951 0.3103
Para wise 1 0.3241 0.3655 0.3436
2 0.3475 0.3491 0.3483
Para wise proposition 1 0.3453 0.3445 0.3449
2 0.3225 0.3604 0.3404
Ensemble 1 0.3668 0.4053 0.3851
2 0.3961 0.3934 0.3948

Dataset Link: Link

Copyright info

© 2025 Kriti Arora, Bhavya Jain, Chetan Arora. All rights reserved.

About

We introduce a citation-neighbourhood retrieval framework that represents each case using compact textual segments surrounding citation markers. On this fil- tered set, we compute similarity-based features and assign relevance scores through an ensemble classifier combining a Multi-Layer Per- ceptron and a Random Forest model. In COLIEE 2025 Task 1

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