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...
Attention Head Entropy of LLMs Predicts Answer Correctness
arXiv:2602.13699v1 Announce Type: new Abstract: Large language models (LLMs) often generate plausible yet incorrect answers, posing risks in safety-critical settings such as medicine. Human evaluation is expensive, and LLM-as-judge approaches risk introducing hidden errors. Recent white-box methods detect contextual hallucinations...
On Representation Redundancy in Large-Scale Instruction Tuning Data Selection
arXiv:2602.13773v1 Announce Type: new Abstract: Data quality is a crucial factor in large language models training. While prior work has shown that models trained on smaller, high-quality datasets can outperform those trained on much larger but noisy or low-quality corpora,...
MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models
arXiv:2602.13783v1 Announce Type: new Abstract: While Time Series Foundation Models (TSFMs) have demonstrated exceptional performance in generalized forecasting, their performance often degrades significantly when deployed in real-world vertical domains characterized by temporal distribution shifts and domain-specific periodic structures. Current solutions...
Cast-R1: Learning Tool-Augmented Sequential Decision Policies for Time Series Forecasting
arXiv:2602.13802v1 Announce Type: new Abstract: Time series forecasting has long been dominated by model-centric approaches that formulate prediction as a single-pass mapping from historical observations to future values. Despite recent progress, such formulations often struggle in complex and evolving settings,...
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...
Sufficient Conditions for Stability of Minimum-Norm Interpolating Deep ReLU Networks
arXiv:2602.13910v1 Announce Type: new Abstract: Algorithmic stability is a classical framework for analyzing the generalization error of learning algorithms. It predicts that an algorithm has small generalization error if it is insensitive to small perturbations in the training set such...
A Multi-Agent Framework for Code-Guided, Modular, and Verifiable Automated Machine Learning
arXiv:2602.13937v1 Announce Type: new Abstract: Automated Machine Learning (AutoML) has revolutionized the development of data-driven solutions; however, traditional frameworks often function as "black boxes", lacking the flexibility and transparency required for complex, real-world engineering tasks. Recent Large Language Model (LLM)-based...
Is the Electronic Trade Documents Act 2023 Sufficient to Promote the Uptake of Paperless Trading Systems?
In September 2023, the Electronic Trade Documents Act (ETDA) came into force in the UK. It aims to facilitate paperless trade by allowing certain trade documents in electronic form to have the same legal functionality as their paper counterparts. The...
Review of Hanna Schebesta and Kai Purnhagen, EU Food Law, Oxford, Oxford University Press, 2024, 432 pp, hb, £110.00
Anyone interested in food system reform should acknowledge the importance of EU law and learn to recognise its strengths and weaknesses, so as to fully harness its transformative potential. This is no easy task, for EU food law is a...
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...
The Shareholder's Standing to Challenge the Exercise of Directorial Power: Tianrui (International) Holding Company Ltd v China Shanshui Cement Group Ltd
An enduring problem with the proper purposes duty is the apparent right of the shareholder to enforce the same despite the duty being owed to the company. The cases on the proper purpose duty have thus far simply assumed the...
Navigating the Evolving Landscape of Enterprise AI Governance and Compliance
The rapid adoption of Artificial Intelligence (AI) across enterprises has ushered in a new era of innovation and efficiency, but it also poses significant governance and compliance challenges. As of February 2026, regulatory bodies and industry leaders are responding with...