Effectual Contract Management and Analysis with AI-Powered Technology: Reducing Errors and Saving Time in Legal Document
Examining the revolutionary effects of AI-powered tools in the field of contract analysis and management for legal document inspection is the focus of this study. The purpose of this research is to experimentally explore the likelihood of efficiency benefits and...
AI-Driven Legal Automation to Enhance Legal Processes with Natural Language Processing
The legal sector often faces delays and inefficiencies due to the overwhelming volume of information, the labor-intensive nature of research, and high service costs. This paper introduces a novel framework for AI-driven legal automation, which employs Natural Language Processing (NLP)...
Justices to consider constitutionality of tax foreclosure sales
The argument next week in Pung v Isabella County asks the court to consider the constitutionality of the longstanding practice of tax foreclosures sales. This is one of those cases […]The postJustices to consider constitutionality of tax foreclosure salesappeared first...
SCOTUStoday for Friday, February 20
Good morning, and welcome to what is likely to be the first opinion day of the month, as the justices reconvene after their winter recess. We will be live blogging […]The postSCOTUStoday for Friday, February 20appeared first onSCOTUSblog.
FCC asks stations for "pro-America" programming, like daily Pledge of Allegiance
Brendan Carr wants "patriotic" shows for Trump's yearlong America 250 celebration.
Supreme Court blocks Trump's emergency tariffs, billions in refunds may be owed
Economists estimated more than $175 billion may need to be refunded.
The creator economy’s ad revenue problem and India’s AI ambitions
The creator economy is evolving fast, and ad revenue alone isn’t cutting it anymore. YouTubers are launching product lines, acquiring startups, and building actual business empires. In fact, MrBeast’s company bought fintech startup Step, and his chocolate business is outearning...
Resp-Agent: An Agent-Based System for Multimodal Respiratory Sound Generation and Disease Diagnosis
arXiv:2602.15909v1 Announce Type: cross Abstract: Deep learning-based respiratory auscultation is currently hindered by two fundamental challenges: (i) inherent information loss, as converting signals into spectrograms discards transient acoustic events and clinical context; (ii) limited data availability, exacerbated by severe class...
Reranker Optimization via Geodesic Distances on k-NN Manifolds
arXiv:2602.15860v1 Announce Type: new Abstract: Current neural reranking approaches for retrieval-augmented generation (RAG) rely on cross-encoders or large language models (LLMs), requiring substantial computational resources and exhibiting latencies of 3-5 seconds per query. We propose Maniscope, a geometric reranking method...
CheckIfExist: Detecting Citation Hallucinations in the Era of AI-Generated Content
arXiv:2602.15871v1 Announce Type: new Abstract: The proliferation of large language models (LLMs) in academic workflows has introduced unprecedented challenges to bibliographic integrity, particularly through reference hallucination -- the generation of plausible but non-existent citations. Recent investigations have documented the presence...
DocSplit: A Comprehensive Benchmark Dataset and Evaluation Approach for Document Packet Recognition and Splitting
arXiv:2602.15958v1 Announce Type: new Abstract: Document understanding in real-world applications often requires processing heterogeneous, multi-page document packets containing multiple documents stitched together. Despite recent advances in visual document understanding, the fundamental task of document packet splitting, which involves separating a...
The Validity of Coreference-based Evaluations of Natural Language Understanding
arXiv:2602.16200v1 Announce Type: new Abstract: In this thesis, I refine our understanding as to what conclusions we can reach from coreference-based evaluations by expanding existing evaluation practices and considering the extent to which evaluation results are either converging or conflicting....
R$^2$Energy: A Large-Scale Benchmark for Robust Renewable Energy Forecasting under Diverse and Extreme Conditions
arXiv:2602.15961v1 Announce Type: new Abstract: The rapid expansion of renewable energy, particularly wind and solar power, has made reliable forecasting critical for power system operations. While recent deep learning models have achieved strong average accuracy, the increasing frequency and intensity...
Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training
arXiv:2602.16065v1 Announce Type: new Abstract: Generative Artificial Intelligence (AI), such as large language models (LLMs), has become a transformative force across science, industry, and society. As these systems grow in popularity, web data becomes increasingly interwoven with this AI-generated material...
Omni-iEEG: A Large-Scale, Comprehensive iEEG Dataset and Benchmark for Epilepsy Research
arXiv:2602.16072v1 Announce Type: new Abstract: Epilepsy affects over 50 million people worldwide, and one-third of patients suffer drug-resistant seizures where surgery offers the best chance of seizure freedom. Accurate localization of the epileptogenic zone (EZ) relies on intracranial EEG (iEEG)....
On the Power of Source Screening for Learning Shared Feature Extractors
arXiv:2602.16125v1 Announce Type: new Abstract: Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneous sources. Most existing work includes all related data sources via simultaneously training a common feature extractor...
HiPER: Hierarchical Reinforcement Learning with Explicit Credit Assignment for Large Language Model Agents
arXiv:2602.16165v1 Announce Type: new Abstract: Training LLMs as interactive agents for multi-turn decision-making remains challenging, particularly in long-horizon tasks with sparse and delayed rewards, where agents must execute extended sequences of actions before receiving meaningful feedback. Most existing reinforcement learning...
Towards Secure and Scalable Energy Theft Detection: A Federated Learning Approach for Resource-Constrained Smart Meters
arXiv:2602.16181v1 Announce Type: new Abstract: Energy theft poses a significant threat to the stability and efficiency of smart grids, leading to substantial economic losses and operational challenges. Traditional centralized machine learning approaches for theft detection require aggregating user data, raising...
Linked Data Classification using Neurochaos Learning
arXiv:2602.16204v1 Announce Type: new Abstract: Neurochaos Learning (NL) has shown promise in recent times over traditional deep learning due to its two key features: ability to learn from small sized training samples, and low compute requirements. In prior work, NL...
Democrats ask Supreme Court not to disrupt New York redistricting dispute
Two separate groups of New York voters and elected officials on Thursday afternoon urged the Supreme Court to leave in place a ruling by a state trial judge in Manhattan […]The postDemocrats ask Supreme Court not to disrupt New York...
Can courts excuse late removals to federal court?
As many law students learn in their civil procedure course, when a plaintiff files suit in state court asserting a claim over which a federal district court would have jurisdiction, […]The postCan courts excuse late removals to federal court?appeared first...
What the Justice Department overlooks in its historical argument to end birthright citizenship
Immigration Matters is a recurring series by César Cuauhtémoc García Hernández that analyzes the court’s immigration docket, highlighting emerging legal questions about new policy and enforcement practices. In my last […]The postWhat the Justice Department overlooks in its historical argument...
SCOTUStoday for Thursday, February 19
Updated on Feb. 19 at 9:50 a.m. President Franklin D. Roosevelt issued Executive Order 9066 on this day in 1942, authorizing the removal of Japanese Americans to internment camps. In […]The postSCOTUStoday for Thursday, February 19appeared first onSCOTUSblog.
“Open & Close Strategy”: How Japanese Tech Companies with Niche Technologies Can Leverage IP for Competitive Advantage
Tomotaka Hosokawa, LL.M. Class of 2026 The Strategy The “Open & Close Strategy” refers to a business and intellectual property strategy where a Japanese technology company intentionally “opens” specific technologies to expand the market while simultaneously “closing” other technologies to...
Reddit is testing a new AI search feature for shopping
A small group of users in the U.S. will start to see search results that include interactive product carousels with pricing, images, and direct where-to-buy links.
ER-MIA: Black-Box Adversarial Memory Injection Attacks on Long-Term Memory-Augmented Large Language Models
arXiv:2602.15344v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly augmented with long-term memory systems to overcome finite context windows and enable persistent reasoning across interactions. However, recent research finds that LLMs become more vulnerable because memory provides extra...
Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits
arXiv:2602.15405v1 Announce Type: new Abstract: Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancement and classification as separate, sequential stages: first enhancing the signal and then applying a classifier. This approach...
Neural Network-Based Parameter Estimation of a Labour Market Agent-Based Model
arXiv:2602.15572v1 Announce Type: new Abstract: Agent-based modelling (ABM) is a widespread approach to simulate complex systems. Advancements in computational processing and storage have facilitated the adoption of ABMs across many fields; however, ABMs face challenges that limit their use as...
CVPR 2026 Compute Reporting Form - Clarification