Diffusion Modulation via Environment Mechanism Modeling for Planning
arXiv:2602.20422v1 Announce Type: new Abstract: Diffusion models have shown promising capabilities in trajectory generation for planning in offline reinforcement learning (RL). However, conventional diffusion-based planning methods often fail to account for the fact that generating trajectories in RL requires unique...
KairosVL: Orchestrating Time Series and Semantics for Unified Reasoning
arXiv:2602.20494v1 Announce Type: new Abstract: Driven by the increasingly complex and decision-oriented demands of time series analysis, we introduce the Semantic-Conditional Time Series Reasoning task, which extends conventional time series analysis beyond purely numerical modeling to incorporate contextual and semantic...
CausalReasoningBenchmark: A Real-World Benchmark for Disentangled Evaluation of Causal Identification and Estimation
arXiv:2602.20571v1 Announce Type: new Abstract: Many benchmarks for automated causal inference evaluate a system's performance based on a single numerical output, such as an Average Treatment Effect (ATE). This approach conflates two distinct steps in causal analysis: identification-formulating a valid...
Physics-based phenomenological characterization of cross-modal bias in multimodal models
arXiv:2602.20624v1 Announce Type: new Abstract: The term 'algorithmic fairness' is used to evaluate whether AI models operate fairly in both comparative (where fairness is understood as formal equality, such as "treat like cases as like") and non-comparative (where unfairness arises...
Online Algorithms with Unreliable Guidance
arXiv:2602.20706v1 Announce Type: new Abstract: This paper introduces a new model for ML-augmented online decision making, called online algorithms with unreliable guidance (OAG). This model completely separates between the predictive and algorithmic components, thus offering a single well-defined analysis framework...
CG-DMER: Hybrid Contrastive-Generative Framework for Disentangled Multimodal ECG Representation Learning
arXiv:2602.21154v1 Announce Type: new Abstract: Accurate interpretation of electrocardiogram (ECG) signals is crucial for diagnosing cardiovascular diseases. Recent multimodal approaches that integrate ECGs with accompanying clinical reports show strong potential, but they still face two main concerns from a modality...
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...
The Discrimination Presumption
ARTICLE The Discrimination Presumption Joseph A. Seiner* Employment discrimination is a fact in our society. Scientific studies continue to show that employer misconduct in the workplace is pervasive. This social science research is further supported by governmental data and litigation...
The New Oral Argument: Justices as Advocates
ARTICLE The New Oral Argument: Justices as Advocates Tonja Jacobi* & Matthew Sag** This Article conducts a comprehensive empirical inquiry of fifty-five years of Supreme Court oral argument, showing that judicial activity has increased dramatically, in terms of words used,...
Transborder Speech
ARTICLE Transborder Speech Ronald J. Krotoszynski, Jr.* In an increasingly globalized marketplace of ideas, First Amendment law and theory must recognize that the freedom of speech does not end at the water’s edge. Simply put, the locus of expressive activity...
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.
Autonomous Vehicles and Liability: Who Is Responsible When AI Drives?
As autonomous vehicles approach widespread deployment, legal frameworks for determining liability in accidents involving self-driving cars remain uncertain.
ACAR: Adaptive Complexity Routing for Multi-Model Ensembles with Auditable Decision Traces
arXiv:2602.21231v1 Announce Type: cross Abstract: We present ACAR (Adaptive Complexity and Attribution Routing), a measurement framework for studying multi-model orchestration under auditable conditions. ACAR uses self-consistency variance (sigma) computed from N=3 probe samples to route tasks across single-model, two-model, and...
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...
How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?
arXiv:2602.22441v1 Announce Type: new Abstract: Latent reasoning has been recently proposed as a reasoning paradigm and performs multi-step reasoning through generating steps in the latent space instead of the textual space. This paradigm enables reasoning beyond discrete language tokens by...
CWM: Contrastive World Models for Action Feasibility Learning in Embodied Agent Pipelines
arXiv:2602.22452v1 Announce Type: new Abstract: A reliable action feasibility scorer is a critical bottleneck in embodied agent pipelines: before any planning or reasoning occurs, the agent must identify which candidate actions are physically executable in the current state. Existing approaches...
Mapping the Landscape of Artificial Intelligence in Life Cycle Assessment Using Large Language Models
arXiv:2602.22500v1 Announce Type: new Abstract: Integration of artificial intelligence (AI) into life cycle assessment (LCA) has accelerated in recent years, with numerous studies successfully adapting machine learning algorithms to support various stages of LCA. Despite this rapid development, comprehensive and...
Agentic AI for Intent-driven Optimization in Cell-free O-RAN
arXiv:2602.22539v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is emerging as a key enabler for autonomous radio access networks (RANs), where multiple large language model (LLM)-based agents reason and collaborate to achieve operator-defined intents. The open RAN (O-RAN) architecture...
Knob: A Physics-Inspired Gating Interface for Interpretable and Controllable Neural Dynamics
arXiv:2602.22702v1 Announce Type: new Abstract: Existing neural network calibration methods often treat calibration as a static, post-hoc optimization task. However, this neglects the dynamic and temporal nature of real-world inference. Moreover, existing methods do not provide an intuitive interface enabling...
Know What You Know: Metacognitive Entropy Calibration for Verifiable RL Reasoning
arXiv:2602.22751v1 Announce Type: new Abstract: Large reasoning models (LRMs) have emerged as a powerful paradigm for solving complex real-world tasks. In practice, these models are predominantly trained via Reinforcement Learning with Verifiable Rewards (RLVR), yet most existing outcome-only RLVR pipelines...
MiroFlow: Towards High-Performance and Robust Open-Source Agent Framework for General Deep Research Tasks
arXiv:2602.22808v1 Announce Type: new Abstract: Despite the remarkable progress of large language models (LLMs), the capabilities of standalone LLMs have begun to plateau when tackling real-world, complex tasks that require interaction with external tools and dynamic environments. Although recent agent...
The AI Research Assistant: Promise, Peril, and a Proof of Concept
arXiv:2602.22842v1 Announce Type: new Abstract: Can artificial intelligence truly contribute to creative mathematical research, or does it merely automate routine calculations while introducing risks of error? We provide empirical evidence through a detailed case study: the discovery of novel error...
Obscure but Effective: Classical Chinese Jailbreak Prompt Optimization via Bio-Inspired Search
arXiv:2602.22983v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly used, their security risks have drawn increasing attention. Existing research reveals that LLMs are highly susceptible to jailbreak attacks, with effectiveness varying across language contexts. This paper investigates...
Mind the Gap in Cultural Alignment: Task-Aware Culture Management for Large Language Models
arXiv:2602.22475v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in culturally sensitive real-world tasks. However, existing cultural alignment approaches fail to align LLMs' broad cultural values with the specific goals of downstream tasks and suffer from cross-culture...
Sydney Telling Fables on AI and Humans: A Corpus Tracing Memetic Transfer of Persona between LLMs
arXiv:2602.22481v1 Announce Type: new Abstract: The way LLM-based entities conceive of the relationship between AI and humans is an important topic for both cultural and safety reasons. When we examine this topic, what matters is not only the model itself...
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...
Trump moves to ban Anthropic from the US government
The Defense Department pressured Anthropic to drop restrictions on how its AI can be used by the military.
ESG Investing Under Scrutiny: Legal and Regulatory Developments in 2026
ESG investing faces both increased regulatory support in some jurisdictions and political backlash in others, creating a complex compliance landscape.
The Rise of AI-Powered Legal Research: Transforming How Lawyers Work
AI-powered legal research tools are fundamentally changing the practice of law, offering unprecedented efficiency while raising questions about quality and oversight.