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...
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...
Correcting Human Labels for Rater Effects in AI Evaluation: An Item Response Theory Approach
arXiv:2602.22585v1 Announce Type: new Abstract: Human evaluations play a central role in training and assessing AI models, yet these data are rarely treated as measurements subject to systematic error. This paper integrates psychometric rater models into the AI pipeline to...
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...
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...
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...
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...
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.
AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors
arXiv:2602.22755v1 Announce Type: new Abstract: We introduce AuditBench, an alignment auditing benchmark. AuditBench consists of 56 language models with implanted hidden behaviors. Each model has one of 14 concerning behaviors--such as sycophantic deference, opposition to AI regulation, or secret geopolitical...
Towards Better RL Training Data Utilization via Second-Order Rollout
arXiv:2602.22765v1 Announce Type: new Abstract: Reinforcement Learning (RL) has empowered Large Language Models (LLMs) with strong reasoning capabilities, but vanilla RL mainly focuses on generation capability improvement by training with only first-order rollout (generating multiple responses for a question), and...
Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
arXiv:2602.22871v1 Announce Type: new Abstract: Reasoning with large language models often benefits from generating multiple chains-of-thought, but existing aggregation strategies are typically trajectory-level (e.g., selecting the best trace or voting on the final answer), discarding useful intermediate work from partial...
Quantity Convergence, Quality Divergence: Disentangling Fluency and Accuracy in L2 Mandarin Prosody
arXiv:2602.23071v1 Announce Type: new Abstract: While second language (L2) learners may acquire target syntactic word order, mapping this syntax onto appropriate prosodic structures remains a persistent challenge. This study investigates the fossilization and stability of the L2 syntax-prosody interface by...
Causal Direction from Convergence Time: Faster Training in the True Causal Direction
arXiv:2602.22254v1 Announce Type: new Abstract: We introduce Causal Computational Asymmetry (CCA), a principle for causal direction identification based on optimization dynamics in which one neural network is trained to predict $Y$ from $X$ and another to predict $X$ from $Y$,...
AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning
arXiv:2602.22268v1 Announce Type: new Abstract: Quantization followed by parameter-efficient fine-tuning has emerged as a promising paradigm for downstream adaptation under tight GPU memory constraints. However, this sequential pipeline fails to leverage the intricate interaction between quantization bit-width and LoRA rank....
Positional-aware Spatio-Temporal Network for Large-Scale Traffic Prediction
arXiv:2602.22274v1 Announce Type: new Abstract: Traffic flow forecasting has emerged as an indispensable mission for daily life, which is required to utilize the spatiotemporal relationship between each location within a time period under a graph structure to predict future flow....
BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning
arXiv:2602.22284v1 Announce Type: new Abstract: Recent advancements in deep learning have actively addressed complex challenges within the Computer-Aided Design (CAD) domain.However, most existing approaches rely on task-specifi c models requiring structural modifi cations for new tasks, and they predominantly focus...
A Learning-Based Hybrid Decision Framework for Matching Systems with User Departure Detection
arXiv:2602.22412v1 Announce Type: new Abstract: In matching markets such as kidney exchanges and freight exchanges, delayed matching has been shown to improve overall market efficiency. The benefits of delay are highly sensitive to participants' sojourn times and departure behavior, and...
ECHO: Encoding Communities via High-order Operators
arXiv:2602.22446v1 Announce Type: new Abstract: Community detection in attributed networks faces a fundamental divide: topological algorithms ignore semantic features, while Graph Neural Networks (GNNs) encounter devastating computational bottlenecks. Specifically, GNNs suffer from a Semantic Wall of feature over smoothing in...
United States v. Hemani: an animated explainer
SCOTUSblog is thrilled to introduce the first in a series of animated videos, done in partnership with Briefly, on some of the most important upcoming cases of the 2025-26 term. Today’s […]The postUnited States v. Hemani: an animated explainerappeared first...
SCOTUStoday for Friday, February 27
We’re thrilled to introduce the first in a series of animated videos, done in partnership with Briefly, on some of the most important upcoming cases of the current term. This first […]The postSCOTUStoday for Friday, February 27appeared first onSCOTUSblog.
Breakthrough in Quantum-Resistant Cryptography: Preparing for the Post-Quantum Era
NIST has finalized post-quantum cryptography standards, but the transition to quantum-resistant systems presents immense technical and organizational challenges.
Mitigating Structural Noise in Low-Resource S2TT: An Optimized Cascaded Nepali-English Pipeline with Punctuation Restoration
arXiv:2602.21647v1 Announce Type: new Abstract: This paper presents and evaluates an optimized cascaded Nepali speech-to-English text translation (S2TT) system, focusing on mitigating structural noise introduced by Automatic Speech Recognition (ASR). We first establish highly proficient ASR and NMT components: a...
RADAR: Reasoning as Discrimination with Aligned Representations for LLM-based Knowledge Graph Reasoning
arXiv:2602.21951v1 Announce Type: new Abstract: Knowledge graph reasoning (KGR) infers missing facts, with recent advances increasingly harnessing the semantic priors and reasoning abilities of Large Language Models (LLMs). However, prevailing generative paradigms are prone to memorizing surface-level co-occurrences rather than...
Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting
arXiv:2602.21498v1 Announce Type: new Abstract: Irregular Multivariate Time Series (IMTS) are characterized by uneven intervals between consecutive timestamps, which carry sampling pattern information valuable and informative for learning temporal and variable dependencies. In addition, IMTS often exhibit diverse dependencies across...
Training-free Composition of Pre-trained GFlowNets for Multi-Objective Generation
arXiv:2602.21565v1 Announce Type: new Abstract: Generative Flow Networks (GFlowNets) learn to sample diverse candidates in proportion to a reward function, making them well-suited for scientific discovery, where exploring multiple promising solutions is crucial. Further extending GFlowNets to multi-objective settings has...
Copyright’s Invisible Hand: Subsidizing America’s Cultural Institutions
The doctrine of copyright exhaustion conceals a substantial and underappreciated subsidy at the heart of American copyright law. For more than a century, it has operated as a deliberate congressional scheme transferring billions of dollars in value to cultural institutions,...
Court to hear argument on whether and when drug users may possess firearms
The Supreme Court will hear oral arguments on Monday in United States v. Hemani, the second gun-rights case of the 2025-26 term. In January, the Trump administration supported Hawaii gun […]The postCourt to hear argument on whether and when drug...