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...
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...
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...
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...
Importance of Prompt Optimisation for Error Detection in Medical Notes Using Language Models
arXiv:2602.22483v1 Announce Type: new Abstract: Errors in medical text can cause delays or even result in incorrect treatment for patients. Recently, language models have shown promise in their ability to automatically detect errors in medical text, an ability that has...
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...
Waging the Battle for Society’s Soul: The Constitutionality of Juvenile Transfer Legislation in the Wake of Jones v. Mississippi lawreview - Minnesota Law Review
By LOGAN KNUTSON. Full Text. Trying juvenile defendants as adults is a cruel, yet enduring practice in U.S. criminal law. If convicted, these youthful offenders face brutal conditions in adult prison and a lifelong stigma. Although these devastating consequences of...
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...
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.
Zero-Day Vulnerabilities in Enterprise AI Systems: Legal and Technical Implications
The discovery of critical zero-day vulnerabilities in widely deployed AI systems raises urgent questions about cybersecurity liability and disclosure obligations.
Tokenization, Fusion and Decoupling: Bridging the Granularity Mismatch Between Large Language Models and Knowledge Graphs
arXiv:2602.22698v1 Announce Type: new Abstract: Leveraging Large Language Models (LLMs) for Knowledge Graph Completion (KGC) is promising but hindered by a fundamental granularity mismatch. LLMs operate on fragmented token sequences, whereas entities are the fundamental units in knowledge graphs (KGs)...
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...
Deep Sequence Modeling with Quantum Dynamics: Language as a Wave Function
arXiv:2602.22255v1 Announce Type: new Abstract: We introduce a sequence modeling framework in which the latent state is a complex-valued wave function evolving on a finite-dimensional Hilbert space under a learned, time-dependent Hamiltonian. Unlike standard recurrent architectures that rely on gating...
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....
Structure and Redundancy in Large Language Models: A Spectral Study via Random Matrix Theory
arXiv:2602.22345v1 Announce Type: new Abstract: This thesis addresses two persistent and closely related challenges in modern deep learning, reliability and efficiency, through a unified framework grounded in Spectral Geometry and Random Matrix Theory (RMT). As deep networks and large language...
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...
Persistent Nonnegative Matrix Factorization via Multi-Scale Graph Regularization
arXiv:2602.22536v1 Announce Type: new Abstract: Matrix factorization techniques, especially Nonnegative Matrix Factorization (NMF), have been widely used for dimensionality reduction and interpretable data representation. However, existing NMF-based methods are inherently single-scale and fail to capture the evolution of connectivity structures...
Justices appear dubious of challenge to constitutionality of foreclosure sales
The argument yesterday in Pung v Isabella County had two distinct threads. On the one hand, the justices who discussed the question presented seemed to have no doubt that they […]The postJustices appear dubious of challenge to constitutionality of foreclosure...
How strong is New York's "illegal gambling" case against Valve's loot boxes?
Lawyers tell Ars the state has a tough road ahead, even as Valve is uniquely vulnerable.
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.
Neural network optimization strategies and the topography of the loss landscape
arXiv:2602.21276v1 Announce Type: new Abstract: Neural networks are trained by optimizing multi-dimensional sets of fitting parameters on non-convex loss landscapes. Low-loss regions of the landscapes correspond to the parameter sets that perform well on the training data. A key issue...
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...
ABM-UDE: Developing Surrogates for Epidemic Agent-Based Models via Scientific Machine Learning
arXiv:2602.21588v1 Announce Type: new Abstract: Agent-based epidemic models (ABMs) encode behavioral and policy heterogeneity but are too slow for nightly hospital planning. We develop county-ready surrogates that learn directly from exascale ABM trajectories using Universal Differential Equations (UDEs): mechanistic SEIR-family...
How can the Supreme Court protect electoral integrity?
Justice, Democracy, and Law is a recurring series by Edward B. Foley that focuses on election law and the relationship of law and democracy. The court has already confronted cases […]The postHow can the Supreme Court protect electoral integrity?appeared first...
SCOTUStoday for Thursday, February 26
A new Economist/YouGov poll found that 57% of Americans strongly or somewhat approve of the tariffs ruling and 23% disapprove. For more on the survey, see the Morning Reads section […]The postSCOTUStoday for Thursday, February 26appeared first onSCOTUSblog.
HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders
arXiv:2602.21009v1 Announce Type: cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible in production due to latency and memory constraints. While summarizing history via interest centers offers a practical alternative,...
IMOVNO+: A Regional Partitioning and Meta-Heuristic Ensemble Framework for Imbalanced Multi-Class Learning
arXiv:2602.20199v1 Announce Type: new Abstract: Class imbalance, overlap, and noise degrade data quality, reduce model reliability, and limit generalization. Although widely studied in binary classification, these issues remain underexplored in multi-class settings, where complex inter-class relationships make minority-majority structures unclear...
Justices reveal little about whether the deadline for removing cases to federal court can be excused
When a plaintiff files a lawsuit in state court asserting a claim that could be brought in federal court, federal law gives the defendant 30 days to remove the case […]The postJustices reveal little about whether the deadline for removing...
Musk has no proof OpenAI stole xAI trade secrets, judge rules, tossing lawsuit
Even twisting an ex-employee's text to favor xAI's reading fails to sway judge.