Natural Language Processing Models for Robust Document Categorization
arXiv:2602.20336v1 Announce Type: new Abstract: This article presents an evaluation of several machine learning methods applied to automated text classification, alongside the design of a demonstrative system for unbalanced document categorization and distribution. The study focuses on balancing classification accuracy...
Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning
arXiv:2602.20528v1 Announce Type: new Abstract: The Stop-Think-AutoRegress Language Diffusion Model (STAR-LDM) integrates latent diffusion planning with autoregressive generation. Unlike conventional autoregressive language models limited to token-by-token decisions, STAR-LDM incorporates a "thinking" phase that pauses generation to refine a semantic plan...
A Hierarchical Multi-Agent System for Autonomous Discovery in Geoscientific Data Archives
arXiv:2602.21351v1 Announce Type: new Abstract: The rapid accumulation of Earth science data has created a significant scalability challenge; while repositories like PANGAEA host vast collections of datasets, citation metrics indicate that a substantial portion remains underutilized, limiting data reusability. Here...
Prompt Architecture Determines Reasoning Quality: A Variable Isolation Study on the Car Wash Problem
arXiv:2602.21814v1 Announce Type: new Abstract: Large language models consistently fail the "car wash problem," a viral reasoning benchmark requiring implicit physical constraint inference. We present a variable isolation study (n=20 per condition, 6 conditions, 120 total trials) examining which prompt...
2-Step Agent: A Framework for the Interaction of a Decision Maker with AI Decision Support
arXiv:2602.21889v1 Announce Type: new Abstract: Across a growing number of fields, human decision making is supported by predictions from AI models. However, we still lack a deep understanding of the effects of adoption of these technologies. In this paper, we...
Petri Net Relaxation for Infeasibility Explanation and Sequential Task Planning
arXiv:2602.22094v1 Announce Type: new Abstract: Plans often change due to changes in the situation or our understanding of the situation. Sometimes, a feasible plan may not even exist, and identifying such infeasibilities is useful to determine when requirements need adjustment....
The Fundamental Right to Education
ARTICLE The Fundamental Right to Education Derek W. Black* New litigation has revived one of the most important questions of constitutional law: Is education a fundamental right? The Court’s previous answers have been disappointing. While the Court has hinted that...
Google looks to tackle longstanding RCS spam in India — but not alone
Google is integrating carrier-level filtering into RCS in India through a partnership with Airtel to strengthen protections against spam.
Fintech Regulation 2026: Navigating the New Compliance Landscape
The regulatory environment for fintech has evolved dramatically, with new frameworks addressing digital assets, open banking, and AI-driven financial services.
Global Trade Realignment: How Geopolitical Shifts Are Reshaping International Commerce
The global trade landscape is undergoing a fundamental transformation driven by geopolitical tensions, technological competition, and shifting alliances.
ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction Following
arXiv:2602.21228v1 Announce Type: cross Abstract: As applications of large language models (LLMs) become increasingly complex, the demand for robust complex instruction following capabilities is growing accordingly. We argue that a thorough understanding of the instruction itself, especially the latent reasoning...
AngelSlim: A more accessible, comprehensive, and efficient toolkit for large model compression
arXiv:2602.21233v1 Announce Type: cross Abstract: This technical report introduces AngelSlim, a comprehensive and versatile toolkit for large model compression developed by the Tencent Hunyuan team. By consolidating cutting-edge algorithms, including quantization, speculative decoding, token pruning, and distillation. AngelSlim provides a...
A Systematic Review of Algorithmic Red Teaming Methodologies for Assurance and Security of AI Applications
arXiv:2602.21267v1 Announce Type: cross Abstract: Cybersecurity threats are becoming increasingly sophisticated, making traditional defense mechanisms and manual red teaming approaches insufficient for modern organizations. While red teaming has long been recognized as an effective method to identify vulnerabilities by simulating...
Equitable Evaluation via Elicitation
arXiv:2602.21327v1 Announce Type: cross Abstract: Individuals with similar qualifications and skills may vary in their demeanor, or outward manner: some tend toward self-promotion while others are modest to the point of omitting crucial information. Comparing the self-descriptions of equally qualified...
Alignment-Weighted DPO: A principled reasoning approach to improve safety alignment
arXiv:2602.21346v1 Announce Type: cross Abstract: Recent advances in alignment techniques such as Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and Direct Preference Optimization (DPO) have improved the safety of large language models (LLMs). However, these LLMs remain vulnerable...
Towards Controllable Video Synthesis of Routine and Rare OR Events
arXiv:2602.21365v1 Announce Type: cross Abstract: Purpose: Curating large-scale datasets of operating room (OR) workflow, encompassing rare, safety-critical, or atypical events, remains operationally and ethically challenging. This data bottleneck complicates the development of ambient intelligence for detecting, understanding, and mitigating rare...
Small Language Models for Privacy-Preserving Clinical Information Extraction in Low-Resource Languages
arXiv:2602.21374v1 Announce Type: cross Abstract: Extracting clinical information from medical transcripts in low-resource languages remains a significant challenge in healthcare natural language processing (NLP). This study evaluates a two-step pipeline combining Aya-expanse-8B as a Persian-to-English translation model with five open-source...
FIRE: A Comprehensive Benchmark for Financial Intelligence and Reasoning Evaluation
arXiv:2602.22273v1 Announce Type: new Abstract: We introduce FIRE, a comprehensive benchmark designed to evaluate both the theoretical financial knowledge of LLMs and their ability to handle practical business scenarios. For theoretical assessment, we curate a diverse set of examination questions...
ConstraintBench: Benchmarking LLM Constraint Reasoning on Direct Optimization
arXiv:2602.22465v1 Announce Type: new Abstract: Large language models are increasingly applied to operational decision-making where the underlying structure is constrained optimization. Existing benchmarks evaluate whether LLMs can formulate optimization problems as solver code, but leave open a complementary question. Can...
VeRO: An Evaluation Harness for Agents to Optimize Agents
arXiv:2602.22480v1 Announce Type: new Abstract: An important emerging application of coding agents is agent optimization: the iterative improvement of a target agent through edit-execute-evaluate cycles. Despite its relevance, the community lacks a systematic understanding of coding agent performance on this...
MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios
arXiv:2602.22638v1 Announce Type: new Abstract: Route-planning agents powered by large language models (LLMs) have emerged as a promising paradigm for supporting everyday human mobility through natural language interaction and tool-mediated decision making. However, systematic evaluation in real-world mobility settings is...
Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
arXiv:2602.22680v1 Announce Type: new Abstract: Large language models have enabled agents that reason, plan, and interact with tools and environments to accomplish complex tasks. As these agents operate over extended interaction horizons, their effectiveness increasingly depends on adapting behavior to...
FlexMS is a flexible framework for benchmarking deep learning-based mass spectrum prediction tools in metabolomics
arXiv:2602.22822v1 Announce Type: new Abstract: The identification and property prediction of chemical molecules is of central importance in the advancement of drug discovery and material science, where the tandem mass spectrometry technology gives valuable fragmentation cues in the form of...
FactGuard: Agentic Video Misinformation Detection via Reinforcement Learning
arXiv:2602.22963v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have substantially advanced video misinformation detection through unified multimodal reasoning, but they often rely on fixed-depth inference and place excessive trust in internally generated assumptions, particularly in scenarios where critical...
A Fusion of context-aware based BanglaBERT and Two-Layer Stacked LSTM Framework for Multi-Label Cyberbullying Detection
arXiv:2602.22449v1 Announce Type: new Abstract: Cyberbullying has become a serious and growing concern in todays virtual world. When left unnoticed, it can have adverse consequences for social and mental health. Researchers have explored various types of cyberbullying, but most approaches...
Bridging Latent Reasoning and Target-Language Generation via Retrieval-Transition Heads
arXiv:2602.22453v1 Announce Type: new Abstract: Recent work has identified a subset of attention heads in Transformer as retrieval heads, which are responsible for retrieving information from the context. In this work, we first investigate retrieval heads in multilingual contexts. In...
The Innocence Trap lawreview - Minnesota Law Review
By CAITLIN GLASS & JULIAN GREEN. Full Text. What makes a conviction wrongful? Developments in DNA science have led to a wave of exonerations over the past thirty years, revealing sources of error in the criminal legal process. Innocence organizations...
The Skidmore Compromise: Interpreting Skidmore as a Tiebreaker to Preserve Judicial Wisdom in the Era of Loper Bright lawreview - Minnesota Law Review
By MITCHELL ZAIC. Full Text. 'Law must be stable, and yet it cannot stand still.' Here is the great antinomy confronting us at every turn. Rest and motion, unrelieved and unchecked, are equally destructive. The law, like human kind, if...
The Crisis in U.S. Cancer Care: Law, Markets, and Privatization lawreview - Minnesota Law Review
By DANIEL G. AARON. Full Text. Cancer is surging among youth and young adults in the United States, yet, instead of public regulation addressing its root causes, we have outsourced the management of cancer to the private sector. A suite...
Volume 110 – Issue 3 - Minnesota Law Review