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.

Similar Papers

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.
Detecting Legal Citations in United Kingdom Court Judgments (2025.emnlp-main)

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Challenge: citation detection in court judgments is challenging because of the complexity of legal language . citation analysis is critical for many legal applications, but the complexity is not always easy to solve.
Approach: They compare three different models for citation detection in court judgments using the Cambridge Law Corpus . they compare rulebased regular expressions, transformer-based encoders and large language models .
Outcome: The proposed model outperforms the existing models in the citation analysis and analysis of 190 court judgments.
LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law (2025.acl-industry)

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Challenge: Recent efforts focus on automatic summarization of individual cases, which condense the content of a single case, making it easier for legal professionals to grasp key points.
Approach: They propose a pipeline to generate multi-case structured reports using entire body of case law on user-specified topics within the European Court of Human Rights.
Outcome: The proposed pipeline generates structured reports that enhance efficient, scalable legal analysis.
Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts (2022.emnlp-main)

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Challenge: Legal Judgement Prediction systems without expert-informed adjustments can be vulnerable to shallow, distracting surface signals.
Approach: They propose to use domain expertise to identify statistically predictive but legally irrelevant information and adopt adversarial training to prevent it from relying on it.
Outcome: The proposed model aligns better with expert rationales than baseline models . the results are compared with an existing benchmark dataset of human rights cases .
CaseFacts: A Benchmark for Legal Fact-Checking and Precedent Retrieval (2026.acl-long)

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Challenge: Automated Fact-Checking has largely focused on verifying general knowledge against static corpora.
Approach: They propose a benchmark to verify colloquial legal claims against Supreme Court precedents . the benchmark leverages large language models to synthesize claims from expert case summaries . they say the benchmark is a step forward in the field of legal fact verification .
Outcome: The proposed benchmark bridges the gap between layperson assertions and technical jurisprudence while accounting for temporal validity.
Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts (2024.findings-acl)

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Challenge: Prediction with Explanation is the largest expert-annotated dataset for legal judgment prediction and explanation in the Indian context .
Approach: They propose to use an annotated legal judgment prediction corpus to improve models' accuracy . they employ transformer-based models tailored for both general and Indian legal contexts .
Outcome: The proposed system improves the accuracy and explanatory depth of models for legal judgments.
FourCorners: Grounded Thai Legal Research over a Temporal Knowledge Graph (2026.acl-demo)

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Challenge: a new platform addresses five pain points in legal research in Thailand . the tools available to legal practitioners are fragmented and lack a unified tool for cross-referencing, version tracking or structural navigation.
Approach: They propose a platform that addresses five practitioner pain points through three modules built on a temporal legal knowledge graph covering 552K nodes and 6.3M edges.
Outcome: The proposed platform addresses five practitioner pain points through three modules built on a temporal legal knowledge graph covering 552K nodes and 6.3M edges.
LePaRD: A Large-Scale Dataset of Judicial Citations to Precedent (2024.acl-long)

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Challenge: Legal passage retrieval is a practice-oriented task that seeks to predict relevant passages from precedential court decisions given the context of a legal argument.
Approach: They present a dataset which aims to facilitate work on legal passage retrieval . they extensively evaluate various approaches and find classification-based retrieval works best .
Outcome: The proposed dataset aims to facilitate work on legal passage retrieval . it shows that classification-based retrieval seems to work best .
Complex Labelling and Similarity Prediction in Legal Texts: Automatic Analysis of France’s Court of Cassation Rulings (2022.lrec-1)

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Challenge: Detecting divergences in the applications of the law is an important task . divergencies can occur at three levels: within the Cour de Cassation, between trial courts and, more rarely, between a trial court and the Cour of Cassion.
Approach: They propose to provide automatic tools to facilitate the search for similar rulings . they provide automatic keyword sequence generation models and predict keyword sequences based on available texts .
Outcome: The proposed tools improve correlations between the obtained similarities and human judgments of similarity.
CaseSumm: A Large-Scale Dataset for Long-Context Summarization from U.S. Supreme Court Opinions (2025.findings-naacl)

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Challenge: CaseSumm is a dataset for long-context summarization in the legal domain . human groundtruth summaries are often not available for legal summarizing .
Approach: They propose a dataset for long-context summarization that includes SCOTUS opinions and their official summaries.
Outcome: The proposed dataset is the largest open legal case summarization dataset . it outperforms larger models on automatic metrics and human evaluation .

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