# Learning Interpretable Legal Case Retrieval via Knowledge-Guided Case Reformulation

arXiv: https://arxiv.org/abs/2406.19760 · HTML: https://mlsanity.com/paper/2406.19760/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 30 references that are in the map.
- First posted on arXiv 28 Jun 2024.

## Builds on (most cited first, 16 of 16)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Qwen Technical Report](https://mlsanity.com/paper/2309.16609/) (2023)
- [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://mlsanity.com/paper/2004.12832/) (2020)
- [Precise Zero-Shot Dense Retrieval without Relevance Labels](https://mlsanity.com/paper/2212.10496/) (2022)
- [Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents](https://mlsanity.com/paper/2105.03887/) (2021)
- [Deeper Text Understanding for IR with Contextual Neural Language Modeling](https://mlsanity.com/paper/1905.09217/) (2019)
- [End-to-End Neural Ad-hoc Ranking with Kernel Pooling](https://mlsanity.com/paper/1706.06613/) (2017)
- [Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search](https://mlsanity.com/paper/2303.06573/) (2023)
- [SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval](https://mlsanity.com/paper/2304.11370/) (2023)
- [LeCaRDv2: A Large-Scale Chinese Legal Case Retrieval Dataset](https://mlsanity.com/paper/2310.17609/) (2023)
- [LEVEN: A Large-Scale Chinese Legal Event Detection Dataset](https://mlsanity.com/paper/2203.08556/) (2022)
- [Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction](https://mlsanity.com/paper/2207.04182/) (2022)
- [CaseEncoder: A Knowledge-enhanced Pre-trained Model for Legal Case Encoding](https://mlsanity.com/paper/2305.05393/) (2023)
- [Encoded Summarization: Summarizing Documents into Continuous Vector Space for Legal Case Retrieval](https://mlsanity.com/paper/2309.08187/) (2023)
- [Prompt-based Effective Input Reformulation for Legal Case Retrieval](https://mlsanity.com/paper/2309.02962/) (2023)

## Built on by (most cited first, 15 of 15)

- [Large Language Models Meet Legal Artificial Intelligence: A Survey](https://mlsanity.com/paper/2509.09969/) (2025)
- [GuRE:Generative Query REwriter for Legal Passage Retrieval](https://mlsanity.com/paper/2505.12950/) (2025)
- [GLARE: Agentic Reasoning for Legal Judgment Prediction](https://mlsanity.com/paper/2508.16383/) (2025)
- [LegalSearchLM: Rethinking Legal Case Retrieval as Legal Elements Generation](https://mlsanity.com/paper/2505.23832/) (2025)
- [LegalGraphRAG: Multi-Agent Graph Retrieval-Augmented Generation for Reliable Legal Reasoning](https://mlsanity.com/paper/2605.28120/) (2026)
- [DSAS: A Universal Plug-and-Play Framework for Attention Optimization in Multi-Document Question Answering](https://mlsanity.com/paper/2510.12251/) (2025)
- [Segment First, Retrieve Better: Realistic Legal Search via Rhetorical Role-Based Queries](https://mlsanity.com/paper/2508.00679/) (2025)
- [Kernel Affine Hull Machines as Compute-Efficient Encoders for Frozen Semantic Spaces](https://mlsanity.com/paper/2605.02950/) (2026)
- [NeuroSymbolic AI for Legal AI-TRISM: Trustworthy, Reliable, Interpretable, Safe Models](https://mlsanity.com/paper/2606.15646/) (2026)
- [LegalWorld: A Life-Cycle Interactive Environment for Legal Agents](https://mlsanity.com/paper/2606.18728/) (2026)
- [Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVM](https://mlsanity.com/paper/2502.11131/) (2025)
- [GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval](https://mlsanity.com/paper/2604.23779/) (2026)
- [TypedCSIP: Typed Counterfactual Pretraining for Chinese Legislative Conflict Classification](https://mlsanity.com/paper/2605.25474/) (2026)
- [Beyond Topical Similarity: Contrastive Evidence Retrieval with Interpretable Attention Alignment in RAG](https://mlsanity.com/paper/2606.01482/) (2026)
- [UK-PRBENCH: A Paragraph-Level Precedent Retrieval Benchmark for United Kingdom Case Law](https://mlsanity.com/paper/2609.24613/) (2026)

## Abstract (arXiv)

Legal case retrieval for sourcing similar cases is critical in upholding judicial fairness. Different from general web search, legal case retrieval involves processing lengthy, complex, and highly specialized legal documents. Existing methods in this domain often overlook the incorporation of legal expert knowledge, which is crucial for accurately understanding and modeling legal cases, leading to unsatisfactory retrieval performance. This paper introduces KELLER, a legal knowledge-guided case reformulation approach based on large language models (LLMs) for effective and interpretable legal case retrieval. By incorporating professional legal knowledge about crimes and law articles, we enable large language models to accurately reformulate the original legal case into concise sub-facts of crimes, which contain the essential information of the case. Extensive experiments on two legal case retrieval benchmarks demonstrate superior retrieval performance and robustness on complex legal case queries of KELLER over existing methods.