Bridging the Domain Divide: Supervised vs. Zero-Shot Clinical Section Segmentation from MIMIC-III to Obstetrics
arXiv:2602.17513v1 Announce Type: new Abstract: Clinical free-text notes contain vital patient information. They are structured into labelled sections; recognizing these sections has been shown to support clinical decision-making and downstream NLP tasks. In this paper, we advance clinical section segmentation...
Omitted Variable Bias in Language Models Under Distribution Shift
arXiv:2602.16784v1 Announce Type: cross Abstract: Despite their impressive performance on a wide variety of tasks, modern language models remain susceptible to distribution shifts, exhibiting brittle behavior when evaluated on data that differs in distribution from their training data. In this...
FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment
arXiv:2602.17095v1 Announce Type: new Abstract: Parameter-efficient fine-tuning techniques such as low-rank adaptation (LoRA) enable large language models (LLMs) to adapt to downstream tasks efficiently. Federated learning (FL) further facilitates this process by enabling collaborative fine-tuning across distributed clients without sharing...
Anthropic-funded group backs candidate attacked by rival AI super PAC
Dueling pro-AI PACs have centered around backing or targeting one New York congressional bid: Alex Bores, whose RAISE Act requires AI developers to disclose safety protocols and report serious system misuse.
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...
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....
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...
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...
Fast KV Compaction via Attention Matching
arXiv:2602.16284v1 Announce Type: new Abstract: Scaling language models to long contexts is often bottlenecked by the size of the key-value (KV) cache. In deployed settings, long contexts are typically managed through compaction in token space via summarization. However, summarization can...
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...
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.
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
SCOTUStoday for Wednesday, February 18
Justice Anthony Kennedy joined the court on this day in 1988. He served for slightly more than 30 years, retiring on July 31, 2018. SCOTUS Quick Hits Morning Reads A […]The postSCOTUStoday for Wednesday, February 18appeared first onSCOTUSblog.
Microsoft says Office bug exposed customers’ confidential emails to Copilot AI
Microsoft said the bug meant that its Copilot AI chatbot was reading and summarizing paying customers' confidential emails, bypassing data-protection policies.
STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts
arXiv:2602.14265v1 Announce Type: new Abstract: Inference-Time-Compute (ITC) methods like Best-of-N and Tree-of-Thoughts are meant to produce output candidates that are both high-quality and diverse, but their use of high-temperature sampling often fails to achieve meaningful output diversity. Moreover, existing ITC...
Joint Time Series Chain: Detecting Unusual Evolving Trend across Time Series
arXiv:2602.13649v1 Announce Type: new Abstract: Time series chain (TSC) is a recently introduced concept that captures the evolving patterns in large scale time series. Informally, a time series chain is a temporally ordered set of subsequences, in which consecutive subsequences...
Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
arXiv:2602.13670v1 Announce Type: new Abstract: Class-incremental learning (CIL) with pre-trained models (PTMs) faces a critical trade-off between efficient adaptation and long-term stability. While analytic learning enables rapid, recursive closed-form updates, its efficacy is often compromised by accumulated errors and feature...
AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning
arXiv:2602.13807v1 Announce Type: new Abstract: Time series anomaly detection is critical in many real-world applications, where effective solutions must localize anomalous regions and support reliable decision-making under complex settings. However, most existing methods frame anomaly detection as a purely discriminative...
Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
arXiv:2602.13813v1 Announce Type: new Abstract: We introduce Pawsterior, a variational flow-matching framework for improved and extended simulation-based inference (SBI). Many SBI problems involve posteriors constrained by structured domains, such as bounded physical parameters or hybrid discrete-continuous variables, yet standard flow-matching...
Review of Allan C. Hutchinson, Rethinking Legitimacy: Courts, Constitutions and Politics, Oxford, Hart Publishing, 2025, 192 pp, hb, £90.00
The Supreme Courts of the United States of America and the United Kingdom face increased scrutiny, albeit from opposing sides of the political spectrum. Allan C. Hutchinson’s latest book, provides a welcome contribution that interrogates the contemporary positionings of law...