Search: “legal”

arXiv:2607.05764v1 Announce Type: new Abstract: Answering questions over a set of transactional legal documents is most simply done by injecting the whole corpus into the LLM's context window on every

arXiv:2606.28044v1 Announce Type: new Abstract: In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditiona

arXiv:2606.00116v1 Announce Type: cross Abstract: This study introduces a novel architecture of KAN-based BiGRU model for the task of classification and summarization of legal documents in a low-resou

arXiv:2605.24534v1 Announce Type: new Abstract: We present a fully automated pipeline that transforms large collections of court decisions into legal commentaries for statutes - without providing any

arXiv:2604.23809v1 Announce Type: new Abstract: Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity s

arXiv:2601.17230v2 Announce Type: replace Abstract: Automated Fact-Checking has largely focused on verifying general knowledge against static corpora, overlooking high-stakes domains like law where tr

arXiv:2610.04129v1 Announce Type: cross Abstract: We introduce InvestigationWorlds, an agentic environment for legal investigation. We build on an underused artifact of U.S. civil litigation: the summ

arXiv:2610.00287v1 Announce Type: cross Abstract: Identity assurance is the cost a digital system pays for dishonesty and uncertainty: it exists to make acts attributable when not everyone can be trus

arXiv:2609.13535v1 Announce Type: new Abstract: The EU AI Act introduces mandatory requirements for high-risk AI systems with the explicit goal of ensuring the development and operation of trustworthy

arXiv:2607.25605v1 Announce Type: new Abstract: This paper presents a set-theoretic formalization of the classical usuli method of al-Sabr wa al-Taqsim (Examination and Division) for extracting legal

arXiv:2607.04261v1 Announce Type: new Abstract: Current Legal Judgment Prediction (LJP) is constrained by its reliance on post-hoc judicial materials, increasing the likelihood that models perform ret

arXiv:2606.03728v1 Announce Type: new Abstract: Retrieval-augmented generation systems for legal question answering typically retrieve passages based on semantic similarity and provide them to a langu

arXiv:2605.19806v1 Announce Type: cross Abstract: This paper investigates chunking strategies for retrieval-augmented generation on German statutory law, using the German Civil Code as a structured be

arXiv:2605.14890v1 Announce Type: new Abstract: Foundation models tokenize Ukrainian legal text with vastly different efficiency, yet no systematic comparison exists for this domain. We benchmark seve

arXiv:2604.20726v1 Announce Type: cross Abstract: This work explores the role of prompt design and judge selection in LLM-as-a-Judge evaluations of free text legal question answering. We examine wheth

arXiv:2609.20334v1 Announce Type: new Abstract: Traffic regulations are written for human interpretation and therefore rely on shared background knowledge and flexible phrasing, which inherently intro

arXiv:2609.01741v1 Announce Type: new Abstract: Statutes are increasingly parsed by machines before people read them, and the parsers disagree: on Missouri's statutes, two independently written extrac

arXiv:2608.07705v1 Announce Type: new Abstract: Clinical foundation models trained on large-scale patient data are increasingly used for decision support, screening, and public health. As deployment e

arXiv:2606.26111v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) has enabled users to synthesize music with text prompts, combining copyrighted lyrics, AI-composed melodies

arXiv:2605.12505v1 Announce Type: cross Abstract: Autonomous AI systems generate responsibility gaps: consequential actions that cannot be satisfactorily attributed to developers, operators, or users

arXiv:2302.12039v2 Announce Type: replace Abstract: We summarize the current state of the field of NLP & Law with a specific focus on recent technical and substantive developments. To support our anal

arXiv:2604.12308v1 Announce Type: new Abstract: Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires

arXiv:2604.07028v1 Announce Type: cross Abstract: Strategic interaction in adversarial domains such as law, diplomacy, and negotiation is mediated by language, yet most game-theoretic models abstract

arXiv:2610.00353v1 Announce Type: new Abstract: A sound judgment applies the law to established facts and weighs the circumstances in which they arose. However, existing methods swing between rigid st

arXiv:2609.08342v1 Announce Type: new Abstract: World models take multimodal inputs like text, photos, and diagrams to generate dynamic scenes in accordance with the laws of physics, thus opening a co

arXiv:2608.08022v1 Announce Type: new Abstract: Recent incidents involving Artificial Intelligence (AI) agents, which were reported escaping their containment `unintentionally' to gain unauthorized ac

arXiv:2607.23446v1 Announce Type: cross Abstract: A small language model can receive the governing statutory provision and still answer incorrectly. We test whether fine-tuning on examples containing

arXiv:2601.04424v2 Announce Type: replace Abstract: Large language models (LLMs) now support contexts of up to 1M tokens, but their strengths and weaknesses on complex long-context tasks remain unclea

arXiv:2605.14057v1 Announce Type: new Abstract: Most existing dialogue systems are user-driven, primarily designed to fulfill user requests. However, in many critical real-world scenarios, a conversat

arXiv:2604.28087v1 Announce Type: cross Abstract: Rule-based systems remain central in safety-critical domains but often struggle with scalability, brittleness, and goal misspecification. These limita

arXiv:2604.13288v1 Announce Type: new Abstract: We present a unified pipeline for synthesizing high-quality Quechua and Spanish speech for the Peruvian Constitution using three state-of-the-art text-t

arXiv:2609.27678v1 Announce Type: new Abstract: Contract inference requires multiple judgments about a shared document, but aggregate accuracy can conceal changes in the individual decisions. Repeated

arXiv:2609.11101v1 Announce Type: new Abstract: Dispute mediation is essential for maintaining social harmony and resilience, yet developing skilled mediators is costly and time-consuming. Existing LL

arXiv:2602.12639v2 Announce Type: replace Abstract: Legal text generated by large language models (LLMs) can usually achieve reasonable factual accuracy, but it frequently fails to adhere to the speci

arXiv:2608.15428v1 Announce Type: cross Abstract: Multiple-choice benchmarks are graded on whether a model picks the right option, not on whether it needed the question. Measuring that gap takes care:

arXiv:2608.15270v1 Announce Type: new Abstract: Miss a filing deadline by one day and the claim is barred, however strong the case. Computing that deadline is rarely simple: the period runs from a tri

arXiv:2603.04982v3 Announce Type: replace-cross Abstract: Can targeted user training unlock the productive potential of generative artificial intelligence in professional settings? We study this quest

arXiv:2604.22765v1 Announce Type: cross Abstract: The increasing use of artificial intelligence (AI) by public authorities introduces both opportunities for innovation and significant challenges for t

arXiv:2604.12498v1 Announce Type: cross Abstract: We present Lit2Vec, a reproducible workflow for constructing and validating a chemistry corpus from the Semantic Scholar Open Research Corpus using co

arXiv:2605.30497v1 Announce Type: new Abstract: RAG-based legal assistants have been growing in popularity, but LLM hallucinations remain a key issue and potentially undermines justice. While benchmar

arXiv:2610.07223v1 Announce Type: new Abstract: Cricket, often referred to as the 'gentleman's game,' adheres to a strict rule set for both batsmen and bowlers, where each delivery can significantly i

arXiv:2608.22446v1 Announce Type: new Abstract: Metaphors are figurative use of words for conceptual mapping. Metaphor detection in the legal context has been crucial as metaphors are persuasive jurid

arXiv:2607.24449v1 Announce Type: cross Abstract: International recruitment in France requires navigating a layered legal framework absent from existing legal AI benchmarks. We present a publicly avai

arXiv:2608.03898v1 Announce Type: new Abstract: The automatic structural analysis of legal texts is a cornerstone of legal technology, yet the extraction of their logical components remains a signific

arXiv:2604.06737v1 Announce Type: cross Abstract: Large language models have demonstrated remarkable capabilities across a wide range of natural language processing tasks, yet their application in the

arXiv:2610.02792v1 Announce Type: new Abstract: Legal systems are increasingly implemented through software, yet scalable methods for translating legal texts into accurate symbolic representations rem