Multi-level meta-reinforcement learning with skill-based curriculum
arXiv:2603.08773v1 Announce Type: new Abstract: We consider problems in sequential decision making with natural multi-level structure, where sub-tasks are assembled together to accomplish complex goals. Systematically inferring and leveraging hierarchical structure has remained a longstanding challenge; we describe an efficient...
A New Modeling to Feature Selection Based on the Fuzzy Rough Set Theory in Normal and Optimistic States on Hybrid Information Systems
arXiv:2603.08900v1 Announce Type: new Abstract: Considering the high volume, wide variety, and rapid speed of data generation, investigating feature selection methods for big data presents various applications and advantages. By removing irrelevant and redundant features, feature selection reduces data dimensions,...
Sim2Act: Robust Simulation-to-Decision Learning via Adversarial Calibration and Group-Relative Perturbation
arXiv:2603.09053v1 Announce Type: new Abstract: Simulation-to-decision learning enables safe policy training in digital environments without risking real-world deployment, and has become essential in mission-critical domains such as supply chains and industrial systems. However, simulators learned from noisy or biased real-world...
Causally Sufficient and Necessary Feature Expansion for Class-Incremental Learning
arXiv:2603.09145v1 Announce Type: new Abstract: Current expansion-based methods for Class Incremental Learning (CIL) effectively mitigate catastrophic forgetting by freezing old features. However, such task-specific features learned from the new task may collide with the old features. From a causal perspective,...
The Radio-Frequency Transformer for Signal Separation
arXiv:2603.09201v1 Announce Type: new Abstract: We study a problem of signal separation: estimating a signal of interest (SOI) contaminated by an unknown non-Gaussian background/interference. Given the training data consisting of examples of SOI and interference, we show how to build...
Transductive Generalization via Optimal Transport and Its Application to Graph Node Classification
arXiv:2603.09257v1 Announce Type: new Abstract: Many existing transductive bounds rely on classical complexity measures that are computationally intractable and often misaligned with empirical behavior. In this work, we establish new representation-based generalization bounds in a distribution-free transductive setting, where learned...
The how and why of gun control
A Second Opinion is a recurring series by Haley Proctor on the Second Amendment and constitutional litigation. Last Monday, the Supreme Court heard argument in United States v. Hemani. In […]The postThe how and why of gun controlappeared first onSCOTUSblog.
SCOTUSblog’s new podcast partners
SCOTUSblog is excited to announce the addition of podcasts Amarica’s Constitution and Divided Argument to its podcast lineup, joining Advisory Opinions. While both podcasts will maintain their editorial and creative independence, […]The postSCOTUSblog’s new podcast partnersappeared first onSCOTUSblog.
Birthright citizenship: legal takeaways of mice and men and elephants and dogs
Brothers in Law is a recurring series by brothers Akhil and Vikram Amar, with special emphasis on measuring what the Supreme Court says against what the Constitution itself says. For more content from […]The postBirthright citizenship: legal takeaways of mice...
SCOTUStoday for Tuesday, March 10
SCOTUSblog is excited to announce the addition of podcasts Amarica’s Constitution and Divided Argument to its podcast lineup, joining Advisory Opinions. In a new, jam-packed episode, the hosts of all […]The postSCOTUStoday for Tuesday, March 10appeared first onSCOTUSblog.
AI Now Co-ED Amba Kak Gives Remarks Before the UN General Assembly on AI Governance - AI Now Institute
Sandbar secures $23M Series A for its AI note-taking ring
Sandbar aims to ship the Stream, which can be used to take notes, chat with an AI assistant, and for media playback, this summer.
Validation of a Small Language Model for DSM-5 Substance Category Classification in Child Welfare Records
arXiv:2603.06836v1 Announce Type: new Abstract: Background: Recent studies have demonstrated that large language models (LLMs) can perform binary classification tasks on child welfare narratives, detecting the presence or absence of constructs such as substance-related problems, domestic violence, and firearms involvement....
Hierarchical Embedding Fusion for Retrieval-Augmented Code Generation
arXiv:2603.06593v1 Announce Type: new Abstract: Retrieval-augmented code generation often conditions the decoder on large retrieved code snippets. This ties online inference cost to repository size and introduces noise from long contexts. We present Hierarchical Embedding Fusion (HEF), a two-stage approach...
Nw\=ach\=a Mun\=a: A Devanagari Speech Corpus and Proximal Transfer Benchmark for Nepal Bhasha ASR
arXiv:2603.07554v1 Announce Type: new Abstract: Nepal Bhasha (Newari), an endangered language of the Kathmandu Valley, remains digitally marginalized due to the severe scarcity of annotated speech resources. In this work, we introduce Nw\=ach\=a Mun\=a, a newly curated 5.39-hour manually transcribed...
Whitening Reveals Cluster Commitment as the Geometric Separator of Hallucination Types
arXiv:2603.07755v1 Announce Type: new Abstract: A geometric hallucination taxonomy distinguishes three failure types -- center-drift (Type~1), wrong-well convergence (Type~2), and coverage gaps (Type~3) -- by their signatures in embedding cluster space. Prior work found Types~1 and~2 indistinguishable in full-dimensional contextual...
Dual-Metric Evaluation of Social Bias in Large Language Models: Evidence from an Underrepresented Nepali Cultural Context
arXiv:2603.07792v1 Announce Type: new Abstract: Large language models (LLMs) increasingly influence global digital ecosystems, yet their potential to perpetuate social and cultural biases remains poorly understood in underrepresented contexts. This study presents a systematic analysis of representational biases in seven...
Scale Dependent Data Duplication
arXiv:2603.06603v1 Announce Type: new Abstract: Data duplication during pretraining can degrade generalization and lead to memorization, motivating aggressive deduplication pipelines. However, at web scale, it is unclear what constitutes a ``duplicate'': beyond surface-form matches, semantically equivalent documents (e.g. translations) may...
Know When You're Wrong: Aligning Confidence with Correctness for LLM Error Detection
arXiv:2603.06604v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed in critical decision-making systems, the lack of reliable methods to measure their uncertainty presents a fundamental trustworthiness risk. We introduce a normalized confidence score based on output...
Advances in GRPO for Generation Models: A Survey
arXiv:2603.06623v1 Announce Type: new Abstract: Large-scale flow matching models have achieved strong performance across generative tasks such as text-to-image, video, 3D, and speech synthesis. However, aligning their outputs with human preferences and task-specific objectives remains challenging. Flow-GRPO extends Group Relative...
Pavement Missing Condition Data Imputation through Collective Learning-Based Graph Neural Networks
arXiv:2603.06625v1 Announce Type: new Abstract: Pavement condition data is important in providing information regarding the current state of the road network and in determining the needs of maintenance and rehabilitation treatments. However, the condition data is often incomplete due to...
Trust Aware Federated Learning for Secure Bone Healing Stage Interpretation in e-Health
arXiv:2603.06646v1 Announce Type: new Abstract: This paper presents a trust aware federated learning (FL) framework for interpreting bone healing stages using spectral features derived from frequency response data. The primary objective is to address the challenge posed by either unreliable...
HURRI-GAN: A Novel Approach for Hurricane Bias-Correction Beyond Gauge Stations using Generative Adversarial Networks
arXiv:2603.06649v1 Announce Type: new Abstract: The coastal regions of the eastern and southern United States are impacted by severe storm events, leading to significant loss of life and properties. Accurately forecasting storm surge and wind impacts from hurricanes is essential...
ERP-RiskBench: Leakage-Safe Ensemble Learning for Financial Risk
arXiv:2603.06671v1 Announce Type: new Abstract: Financial risk detection in Enterprise Resource Planning (ERP) systems is an important but underexplored application of machine learning. Published studies in this area tend to suffer from vague dataset descriptions, leakage-prone pipelines, and evaluation practices...
Scaling Agentic Capabilities, Not Context: Efficient Reinforcement Finetuning for Large Toolspaces
arXiv:2603.06713v1 Announce Type: new Abstract: Agentic systems operating over large tool ecosystems must plan and execute long-horizon workflows under weak or non-verifiable supervision. While frontier models mitigate these challenges through scale and large context budgets, small language models (SLMs) remain...
ProtAlign: Contrastive learning paradigm for Sequence and structure alignment
arXiv:2603.06722v1 Announce Type: new Abstract: Protein language models often take into consideration the alignment between a protein sequence and its textual description. However, they do not take structural information into consideration. Traditional methods treat sequence and structure separately, limiting the...
Stabilizing Reinforcement Learning for Diffusion Language Models
arXiv:2603.06743v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is highly effective for post-training autoregressive (AR) language models, yet its direct application to diffusion large language models (dLLMs) often triggers reward collapse. We identify two sources of incompatibility. First,...
Court agrees to hear case on environmental laws, does not act on several Second Amendment challenges
Updated on March 9 at 5:14 p.m. The Supreme Court added just one case – a technical dispute over the interaction between two federal environmental laws – to its docket […]The postCourt agrees to hear case on environmental laws, does...
In birthright citizenship case, Justice Department urges court to treat an old concept in a new way
Immigration Matters is a recurring series by César Cuauhtémoc García Hernández that analyzes the court’s immigration docket, highlighting emerging legal questions about new policy and enforcement practices. President Donald Trump’s […]The postIn birthright citizenship case, Justice Department urges court to...
The dissent that believed the Olympics belong to everyone
In Dissent is a recurring series by Anastasia Boden on Supreme Court dissents that have shaped (or reshaped) our country. The Olympics are one of those rare moments when the […]The postThe dissent that believed the Olympics belong to everyoneappeared...