Position: AI for Science Should Treat Measurement-to-Dataset Pipelines as Inference Components - 惯性聚合

推荐订阅源

Comments on: Blog

Schneier on Security

Microsoft Azure Blog

Tor Project blog

Visual Studio Blog

CXSECURITY Database RSS Feed - CXSecurity.com

Threat Intelligence Blog | Flashpoint

罗磊的独立博客

Cisco Talos Blog

Privacy International News Feed

阮一峰的网络日志

博客园 - 三生石上(FineUI控件)

Recorded Future

Hugging Face - Blog

Tailwind CSS Blog

博客园 - 叶小钗

CTFtime.org: upcoming CTF events

LINUX DO - 最新话题

美团技术团队

大猫的无限游戏

博客园 - 司徒正美

酷壳 – CoolShell

钛媒体：引领未来商业与生活新知

宝玉的分享

The Register - Security

Java Code Geeks

Threat Research - Cisco Blogs

The Blog of Author Tim Ferriss

SegmentFault 最新的问题

Fox-IT International blog

Security Archives - TechRepublic

Last Week in AI

MIT News - Artificial intelligence

cs.LG updates on arXiv.org

Learning Laplacian Eigenspace with Mass-Aware Neural Operators on Point Clouds A computational phase transition for learning-to-sample from Ising models Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction LAPLEX: The FFT of Learnable Laplace Kernels LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots Large Language Model Selection with Limited Annotations Assessing the Operational Viability of Foundation Models for Time Series Forecasting CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers Lake Detection and Water Quality Estimation in Sentinel-2 Data Faithfulness as Information Flow: Evaluating and Training Faithful Chain-of-Thought Reasoning A lift for input-convex neural network training LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs Balancing Fairness, Privacy, and Accuracy: A Multitask Adversarial Framework for Centralized Data-Driven Systems CSP-Atlas: Concept-Specific Neural Circuits in a Sparse Python Transformer Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion AvAtar: Learning to Align via Active Optimal Transport Federated Learning over Human-Body Communication for On-Body Edge Intelligence: A Survey, Taxonomy, and BODYFED-HBC Scheduling Vignette Trajectory-Based Difficulty Scoring for Reliable Learning on Tabular Data Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection Omissive Bias in Religious Representation: Benchmarking LLM Answers to Everyday Ethical Decision-making Towards Verifiable Transformers: Solver-Checkable Circuit Explanations Generative OOD-regularized Model-based Policy Optimization Synheart Capacity: A Theory-Driven Physiological Representation of Cognitive Capacity Dynamics from Wearable Signals PrivFusion: A Privacy-preserving Multi-Agent Framework for Harmonizing Distributed Datasets Extracting Training Data from Diffusion Language Models via Infilling Filtered Posterior Mean Collections: A Unified Framework for Analytical Models of Diffusion Generalization Cascade-KDE: Robust Time-Series Restoration under Out-of-Distribution Impulse Corruptions When Reasoning Hurts: Source-Aware Evaluation of Frontier LLMs for Clinical SOAP Note Generation Hardware-Aware Federated Learning for Speech Emotion Recognition DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning Mixture of Complementary Agents for Robust LLM Ensemble Rethinking Federated Unlearning via the Lens of Memorization CAFD: Concept-Aware DNN Fault Detection using VLMs ECHO: Terminal Agents Learn World Models for Free Discovering Lexical Gaps Using Embeddings from Multilingual LLMs Deep ZakaiJ: Structured Filtering for Jump-Diffusion Time Series Forecasting SemanticZip: A Pilot Framework for Lossy Text Compression with LLMs as Semantic Decompressors Truthful Online Preference Aggregation for LLM Fine-Tuning in Mobile Crowdsourcing Beyond Fixed Points: Superpolynomial Capacity of Asymmetric Hopfield Networks Refined Analysis of Entropy-Regularized Actor-Critic Towards a Universal Causal Reasoner Overcoming "Physics Shock" in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference An Effective-Rank Audit of Alignment-Induced Activation Shifts: Confound Control, Constructive Calibration, and Limits BC Protocol: Structured Dual-Expert Dialogue for Eliciting High-Quality Chain-of-Thought Post-Training Data Measuring the Depth of LLM Unlearning via Activation Patching Fourier Feature Pyramids for Physics-Informed Neural Networks Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction Agent-ToM: Learning to Monitor Autonomous LLM Agents via Theory-of-Mind Reasoning Treatment Effect Estimation with Differentiated Networked Effect on Graph Data IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization Private Adaptive Covariance Estimation via Gaussian Graphical Models Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions Algometrics: Forecasting Under Algorithmic Feedback ChaosBench-Logic v2: Evaluating LLM Logical Reasoning over Dynamical Systems at Scale TRACE: A taxonomy-grounded synthetic dataset for teaching-program generation and session interpretation in Applied Behavior Analysis TUBE: Tangent Upper Bound on Evidence for Discrete Diffusion Language Models Not All Transitions Matter: Evidence from PPO From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression GEESE: Genotype-aware End-to-End Spatio-temporal Embedding for Behavioral Phenotyping ChainLearn: A Blockchain-Based Capacity-Aware Framework for Federated Ensemble Learning A general tensor-structured compression scheme for efficient large language models What Are We Actually Decoding? Source Attribution for Non-Invasive Brain-to-Language Retrieval Polymorphism Is Rotation: Operational Mechanistic Interpretability from a Two-Layer Transformer to Pythia-70m The Normalized Maximum Likelihood for Regular Non-Smooth Models: Measure-Theoretic Foundations and Geometric Sampling Momentum Streams for Optimizer-Inspired Transformers Temporal Concept Drift in Legal Judgment Prediction: Neural Baselines Across Three Epochs of Ukrainian Court Decisions RL with Learnable Textual Feedback: A Bilevel Approach Representation-Guided Discrete Molecular Graph Retrosynthesis Beyond the Aggregation Dilemma: Prior-Retaining Decoupled Learning for Multimodal Graphs Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks WLNO: Wavelet-Laplace Neural Operator for Solving Partial Differential Equations Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion PILOT: Policy-Informed Learned Optimization for Adaptive Deep Network Training Feature Learning in Wide Neural Networks under $μ$P: Identifiability and Sparse-Dictionary Decomposition of the Mean-Field Limit A Large-Scale Dataset and Benchmark: Do Protein-Ligand Models Learn Binding Sites or Just Binding Likelihood? Batch Normalization Amplifies Memorization and Privacy Risks Riemannian Archetypal Analysis: Interpretable non-linear data analysis on deformed star distributions Signs Beat Floats: Low-Rank Double-Binary Adaptation for On-Device Fine-Tuning Interdomain Attention: Beyond Token-Level Key-Value Memory Characterizing the Representational Capacity of Neural Processes Evolving Robustness--Exploration Trade-off in Online Reinforcement Learning via Quantile Bayesian Risk MDPs LLMs Show No Signs Of Individuated Metacognition PromptAudit: Auditing Prompt Sensitivity in LLM-Based Vulnerability Detection Optimizing Digital Therapeutic Interventions: Online Learning under Endogenous Adherence Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation Aligning Molecular Graph Explanations with Chemical Identity via InChIfied Invariants Feature Lottery? A Bifurcation Theory of Concept Emergence Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agents Hidden-State Privacy Has an Empty Middle A Unified Python Framework for Direct PPO-based Control of AHUs with Economizer Logic and CO2-Constrained Ventilation On the Stability and Realizability of Recurrent Polynomial Surrogate Ternary Logic Gate Networks Zeroth-Order Nonconvex Nonsmooth Optimization with Heavy-Tailed Noise MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding CAffNet: Hard Constraint-Affine Neural Networks Investigating the Interplay between Contextual and Parametric Chain-of-Thought Faithfulness under Optimization Knowledge Graph Modulated Deep Learning for Limited-Sample Clinical Data Analysis

Position: AI for Science Should Treat Measurement-to-Dataset Pipelines as Inference Components

Ling Zhan, X · 2026-05-26 · via cs.LG updates on arXiv.org

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。原文来自 — 版权归原作者所有。