Transformer self-attention encoder-decoder with multimodal deep learning for response time series forecasting and digital twin support in wind structural health monitoring
arXiv:2604.01712v1 Announce Type: new Abstract: The wind-induced structural response forecasting capabilities of a novel transformer methodology are examined here. The model also provides a digital twin component for bridge structural health monitoring. Firstly, the approach uses the temporal characteristics of...
UK AISI Alignment Evaluation Case-Study
arXiv:2604.00788v1 Announce Type: new Abstract: This technical report presents methods developed by the UK AI Security Institute for assessing whether advanced AI systems reliably follow intended goals. Specifically, we evaluate whether frontier models sabotage safety research when deployed as coding...
Retrospective on PAT x ICML 2026 AI Paper Assistant Program
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Announcement of opinions for Tuesday, March 31
On Tuesday, March 31, we will be live blogging as the court potentially releases opinions in one or more argued cases from the current term. Click here for a list […]The postAnnouncement of opinions for Tuesday, March 31appeared first onSCOTUSblog.
Court repudiates extension of federal supervised release while a defendant absconds
After completing a term of imprisonment, federal criminal defendants often serve terms of supervised release that usually last between one to five years, depending on the offense for which they […]The postCourt repudiates extension of federal supervised release while a...
Prominent Scientists, Faith Leaders, Policymakers and Artists Call for a Prohibition on Superintelligence, as Poll Shows Americans Don’t Want It
Initial signatories include AI pioneers Yoshua Bengio and Geoffrey Hinton, leading media voices Steve Bannon and Glenn Beck, Obama's National Security Advisor Susan Rice, business trailblazers Steve Wozniak and Richard Branson, five Nobel Laureates, former Irish President Mary Robinson, actors...
Future of Life Institute Launches Multimillion Dollar Nationwide AI Regulation Campaign
The Protect What’s Human campaign will push for commonsense AI safety rules at federal and state level
MDKeyChunker: Single-Call LLM Enrichment with Rolling Keys and Key-Based Restructuring for High-Accuracy RAG
arXiv:2603.23533v1 Announce Type: new Abstract: RAG pipelines typically rely on fixed-size chunking, which ignores document structure, fragments semantic units across boundaries, and requires multiple LLM calls per chunk for metadata extraction. We present MDKeyChunker, a three-stage pipeline for Markdown documents...
Kronecker-Structured Nonparametric Spatiotemporal Point Processes
arXiv:2603.23746v1 Announce Type: new Abstract: Events in spatiotemporal domains arise in numerous real-world applications, where uncovering event relationships and enabling accurate prediction are central challenges. Classical Poisson and Hawkes processes rely on restrictive parametric assumptions that limit their ability to...
Probabilistic Geometric Alignment via Bayesian Latent Transport for Domain-Adaptive Foundation Models
arXiv:2603.23783v1 Announce Type: new Abstract: Adapting large-scale foundation models to new domains with limited supervision remains a fundamental challenge due to latent distribution mismatch, unstable optimization dynamics, and miscalibrated uncertainty propagation. This paper introduces an uncertainty-aware probabilistic latent transport framework...
Justices dubious about “harsh” rules for omissions by bankrupt debtors
Yesterday’s argument in Keathley v. Buddy Ayers Construction displayed a bench almost uniformly skeptical of a lower court’s absolute standard for responding to the failure of a debtor in bankruptcy […]The postJustices dubious about “harsh” rules for omissions by bankrupt...
Bernie Sanders and AOC propose a ban on data center construction
Senator Bernie Sanders and Rep. Alexandria Ocasio-Cortez introduced companion legislation to halt construction on new data centers until Congress passes comprehensive AI regulation.
AI Mental Models: Learned Intuition and Deliberation in a Bounded Neural Architecture
arXiv:2603.22561v1 Announce Type: new Abstract: This paper asks whether a bounded neural architecture can exhibit a meaningful division of labor between intuition and deliberation on a classic 64-item syllogistic reasoning benchmark. More broadly, the benchmark is relevant to ongoing debates...
Beyond Binary Correctness: Scaling Evaluation of Long-Horizon Agents on Subjective Enterprise Tasks
arXiv:2603.22744v1 Announce Type: new Abstract: Large language models excel on objectively verifiable tasks such as math and programming, where evaluation reduces to unit tests or a single correct answer. In contrast, real-world enterprise work is often subjective and context-dependent: success...
ABSTRAL: Automatic Design of Multi-Agent Systems Through Iterative Refinement and Topology Optimization
arXiv:2603.22791v1 Announce Type: new Abstract: How should multi-agent systems be designed, and can that design knowledge be captured in a form that is inspectable, revisable, and transferable? We introduce ABSTRAL, a framework that treats MAS architecture as an evolving natural-language...
Intelligence Inertia: Physical Principles and Applications
arXiv:2603.22347v1 Announce Type: new Abstract: While Landauer's principle establishes the fundamental thermodynamic floor for information erasure and Fisher Information provides a metric for local curvature in parameter space, these classical frameworks function effectively only as approximations within regimes of sparse...
DariMis: Harm-Aware Modeling for Dari Misinformation Detection on YouTube
arXiv:2603.22977v1 Announce Type: new Abstract: Dari, the primary language of Afghanistan, is spoken by tens of millions of people yet remains largely absent from the misinformation detection literature. We address this gap with DariMis, the first manually annotated dataset of...
CN-Buzz2Portfolio: A Chinese-Market Dataset and Benchmark for LLM-Based Macro and Sector Asset Allocation from Daily Trending Financial News
arXiv:2603.22305v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly transitioning from static Natural Language Processing (NLP) tasks including sentiment analysis and event extraction to acting as dynamic decision-making agents in complex financial environments. However, the evolution of LLMs...
The Library Theorem: How External Organization Governs Agentic Reasoning Capacity
arXiv:2603.21272v1 Announce Type: new Abstract: Externalized reasoning is already exploited by transformer-based agents through chain-of-thought, but structured retrieval -- indexing over one's own reasoning state -- remains underexplored. We formalize the transformer context window as an I/O page and prove...
Enhancing Safety of Large Language Models via Embedding Space Separation
arXiv:2603.20206v1 Announce Type: new Abstract: Large language models (LLMs) have achieved impressive capabilities, yet ensuring their safety against harmful prompts remains a critical challenge. Recent work has revealed that the latent representations (embeddings) of harmful and safe queries in LLMs...
RedacBench: Can AI Erase Your Secrets?
arXiv:2603.20208v1 Announce Type: new Abstract: Modern language models can readily extract sensitive information from unstructured text, making redaction -- the selective removal of such information -- critical for data security. However, existing benchmarks for redaction typically focus on predefined categories...
Supporting Our Community’s Infrastructure: NeurIPS Foundation’s Donation to OpenReview
AI-Driven Multi-Agent Simulation of Stratified Polyamory Systems: A Computational Framework for Optimizing Social Reproductive Efficiency
arXiv:2603.20678v1 Announce Type: new Abstract: Contemporary societies face a severe crisis of demographic reproduction. Global fertility rates continue to decline precipitously, with East Asian nations exhibiting the most dramatic trends -- China's total fertility rate (TFR) fell to approximately 1.0...
NeurIPS 2026 Evaluations & Datasets FAQ
Interpretable Multiple Myeloma Prognosis with Observational Medical Outcomes Partnership Data
arXiv:2603.20341v1 Announce Type: new Abstract: Machine learning (ML) promises better clinical decision-making, yet opaque model behavior limits the adoption in healthcare. We propose two novel regularization techniques for ensuring the interpretability of ML models trained on real-world data. In particular,...
Announcement of opinions for Wednesday, March 25
On Wednesday, March 25, will be live blogging as the court potentially releases opinions in one or more argued cases from the current term. Click here for a list of […]The postAnnouncement of opinions for Wednesday, March 25appeared first onSCOTUSblog.
Probing to Refine: Reinforcement Distillation of LLMs via Explanatory Inversion
arXiv:2603.19266v1 Announce Type: cross Abstract: Distilling robust reasoning capabilities from large language models (LLMs) into smaller, computationally efficient student models remains an unresolved challenge. Despite recent advances, distilled models frequently suffer from superficial pattern memorization and subpar generalization. To overcome...
Any-Subgroup Equivariant Networks via Symmetry Breaking
arXiv:2603.19486v1 Announce Type: new Abstract: The inclusion of symmetries as an inductive bias, known as equivariance, often improves generalization on geometric data (e.g. grids, sets, and graphs). However, equivariant architectures are usually highly constrained, designed for symmetries chosen a priori,...