Cover Image

Can Causal Discovery Algorithms Help in Generating Legal Arguments?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wasmatkar, Soham, Adhikary, Subinay, Rohan, Rakshit, Guha, Shouvik Kumar, Pyne, Saptarshi, Ghosh, Kripabandhu
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Computational Engineering, Finance, and Science Machine Learning I.2.1; I.5.1
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough?
by: Tormos, Adrian, et al.
Published: (2024)

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction
by: Bogachov, Bogdan, et al.
Published: (2025)

Contrastive Similarity Learning for Market Forecasting: The ContraSim Framework
by: Vinden, Nicholas, et al.
Published: (2025)

Uncovering Population PK Covariates from VAE-Generated Latent Spaces
by: Perazzolo, Diego, et al.
Published: (2025)

Can LLMs Identify Tax Abuse?
by: Blair-Stanek, Andrew, et al.
Published: (2025)

Inductive transfer learning from regression to classification in ECG analysis
by: Jayasundara, Ridma, et al.
Published: (2025)

Deep Convolutional Autoencoder for Assessment of Drive-Cycle Anomalies in Connected Vehicle Sensor Data
by: Geglio, Anthony, et al.
Published: (2022)

Inferring Option Movements Through Residual Transactions: A Quantitative Model
by: von Havighorst, Carl, et al.
Published: (2024)

Cryptogenic stroke and migraine: using probabilistic independence and machine learning to uncover latent sources of disease from the electronic health record
by: Betts, Joshua W., et al.
Published: (2025)

Forecasting Labor Markets with LSTNet: A Multi-Scale Deep Learning Approach
by: Nelson-Archer, Adam, et al.
Published: (2025)

When Reasoning Fails: Evaluating 'Thinking' LLMs for Stock Prediction
by: Sodha, Rakeshkumar H
Published: (2025)

Personalized QoE Prediction: A Demographic-Augmented Machine Learning Framework for 5G Video Streaming Networks
by: Ahmed, Syeda Zunaira, et al.
Published: (2025)

Large Language Models for Patent Classification: Strengths, Trade-offs, and the Long Tail Effect
by: Emer, Lorenzo, et al.
Published: (2026)

Ancient Greek Technology: An Immersive Learning Use Case Described Using a Co-Intelligent Custom ChatGPT Assistant
by: Kasapakis, Vlasis, et al.
Published: (2025)

CORGI: Efficient Pattern Matching With Quadratic Guarantees
by: Weitekamp, Daniel
Published: (2025)

LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters
by: van der Meer, Virgill, et al.
Published: (2026)

Deep Policy Iteration with Integer Programming for Inventory Management
by: Harsha, Pavithra, et al.
Published: (2021)

Volatile Organic Compounds for Stress Detection: A Scoping Review and Exploratory Feasibility Study with Low-Cost Sensors
by: Plintz, Nicolai, et al.
Published: (2025)

Large Language Models for Combinatorial Optimization of Design Structure Matrix
by: Jiang, Shuo, et al.
Published: (2025)

When Hallucination Costs Millions: Benchmarking AI Agents in High-Stakes Adversarial Financial Markets
by: Dai, Zeshi, et al.
Published: (2025)

A Hierarchical conv-LSTM and LLM Integrated Model for Holistic Stock Forecasting
by: Chakraborty, Arya, et al.
Published: (2024)

Fourier Neural Operators for Two-Phase, 2D Mold-Filling Problems Related to Metal Casting
by: Minete, Edgard Moreira, et al.
Published: (2025)

Intelligent Design 4.0: Paradigm Evolution Toward the Agentic AI Era
by: Jiang, Shuo, et al.
Published: (2025)

A Novel Loss Function for Deep Learning Based Daily Stock Trading System
by: Guo, Ruoyu, et al.
Published: (2025)

Design Structure Matrix Modularization with Large Language Models
by: Jiang, Shuo, et al.
Published: (2026)

Linearly-scalable and entropy-optimal learning of nonstationary and nonlinear manifolds
by: Horenko, Illia
Published: (2025)

L-GTA: Latent Generative Modeling for Time Series Augmentation
by: Roque, Luis, et al.
Published: (2025)

Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine
by: Roque, Luis, et al.
Published: (2024)

Analog Circuit Sizing Using Machine Learning Based Transistor Circuit Model
by: Rajeoni, Alireza Bagheri
Published: (2023)

Breaking Negative Cycles: A Reflection-To-Action System For Adaptive Change
by: Kim, Minsol Michelle, et al.
Published: (2026)

Asset Pricing in Pre-trained Transformer
by: Lai, Shanyan
Published: (2025)

Entropy Causal Graphs for Multivariate Time Series Anomaly Detection
by: Febrinanto, Falih Gozi, et al.
Published: (2023)

Enhanced Protein Intrinsic Disorder Prediction Through Dual-View Multiscale Features and Multi-objective Evolutionary Algorithm
by: Wang, Shaokuan, et al.
Published: (2026)

GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
by: Liu, Zehao, et al.
Published: (2025)

NGAT: A Node-level Graph Attention Network for Long-term Stock Prediction
by: Niu, Yingjie, et al.
Published: (2025)

Synthetic Financial Data Generation for Enhanced Financial Modelling
by: Hounwanou, Christophe D., et al.
Published: (2025)

GroundLink: Exploring How Contextual Meeting Snippets Can Close Common Ground Gaps in Editing 3D Scenes for Virtual Production
by: Woo, Gun, et al.
Published: (2026)

Emergence of Quantised Representations Isolated to Anisotropic Functions
by: Bird, George
Published: (2025)

Information-Theoretic Quality Metric of Low-Dimensional Embeddings
by: Gutiérrez-Bernal, Sebastián, et al.
Published: (2025)

A Standardized Benchmark for Multilabel Antimicrobial Peptide Classification
by: Ojeda, Sebastian, et al.
Published: (2025)