AOP-Wiki EMOD 3.0: Data Model Expansions and Content Evaluation Framework for Using Agentic AI to Improve Integration between AOPs and New Approach Methodologies (NAMs) - 惯性聚合

推荐订阅源

博客园 - Franky

Proofpoint News Feed

Palo Alto Networks Blog

Hackread – Cybersecurity News, Data Breaches, AI and More

The Register - Security

Security @ Cisco Blogs

Simon Willison's Weblog

Recorded Future

大猫的无限游戏

Microsoft Research Blog - Microsoft Research

Tailwind CSS Blog

cs.CV updates on arXiv.org

Cyber Security Advisories - MS-ISAC

Application and Cybersecurity Blog

True Tiger Recordings

有赞技术团队

Cisco Talos Blog

Hacker News - Newest: "LLM"

The GitHub Blog

cs.AI updates on arXiv.org

博客园 - 叶小钗

Hugging Face - Blog

Hacker News: Ask HN

Security Archives - TechRepublic

Future of Privacy Forum

PCI Perspectives

Help Net Security

让小产品的独立变现更简单 - ezindie.com

The Blog of Author Tim Ferriss

Netflix TechBlog - Medium

罗磊的独立博客

Apple Machine Learning Research

Security Latest

美团技术团队

博客园 - 三生石上(FineUI控件)

Schneier on Security

CERT Recently Published Vulnerability Notes

cs.AI updates on arXiv.org

Latent-space Attacks for Refusal Evasion in Language Models MindLoom: Composing Thought Modes for Frontier-Level Reasoning Data Synthesis The Shape of Testimony: A Scalable Framework for Oral History Archive Comparison TO-Agents: A Multi-Agent AI Pipeline for Preference-Guided Topology Optimization Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs AttuneBench: A Conversation-Based Benchmark for LLM Emotional Intelligence The Impact of AI Usage and Informativeness on Skill Development in Logical Reasoning Investigating Concept Alignment Using Implausible Category Members The Devil is in the Condition Numbers: Why is GLU Better than non-GLU Structure? Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling PACD-Net: Pseudo-Augmented Contrastive Distillation for Glycemic Control Estimation from SMBG Nonlocal operator learning for fMRI encoding and decoding tasks Less Data, Faster Training: repeating smaller datasets speeds up learning via sampling biases Conformal Selective Acting: Anytime-Valid Risk Control for RLVR-Trained LLMs Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction AGPO: Adaptive Group Policy Optimization with Dual Statistical Feedback Axiomatizing Neural Networks via Pursuit of Subspaces The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering Catching a Moving Subspace: Low-Rank Bandits Beyond Stationarity Self-Training Doesn't Flatten Language -- It Restructures It: Surface Markers Amplify While Deep Syntax Dies Sutra: Tensor-Op RNNs as a Compilation Target for Vector Symbolic Architectures CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning DeCoR: Design and Control Co-Optimization for Urban Streets Using Reinforcement Learning Introspective X Training: Feedback Conditioning Improves Scaling Across all LLM Training Stages Distribution-Aware Reward: Reinforcement Learning over Predictive Distributions for LLM Regression JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QA Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor Machine-Learning-Enhanced Non-Invasive Testing for MASLD Fibrosis: Shallow-Deep Neural Networks Versus FIB-4, Tabular Foundation Models, and Large Language Models Runtime-Certified Bounded-Error Quantized Attention Winfree Oscillatory Neural Network LEAP: A closed-loop framework for perovskite precursor additive discovery Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers Correcting Stochastic Update Bias in Preconditioned Language Model Optimizers PREFINE: Preference-Based Implicit Reward and Cost Fine-Tuning for Safety Alignment DASH: Fast Differentiable Architecture Search for Hybrid Attention in Minutes on a Single GPU SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation Variance Reduction for Expectations with Diffusion Teachers \textit{Stochastic} MeanFlow Policies: One-Step Generative Control with Entropic Mirror Descent On the Regularity and Generalization of One-Step Wasserstein-guided Generative Models for PDE-Induced Measures FusionCell: Cross-Attentive Fusion of Layout Geometry and Netlist Topology for Standard-Cell Performance Prediction Smaller Abstract State Spaces Enable Cross-Scale Generalization in Reinforcement Learning Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine Pseudo-Siamese Network for Planning in Target-Oriented Proactive Dialogues Complementing reinforcement learning with SFT through logit averaging in the post training of LLMs Robust Subspace-Constrained Quadratic Models for Low-Dimensional Structure Learning Data-Efficient Neural Operator Training via Physics-Based Active Learning Mechanisms of Misgeneralization in Physical Sequence Modeling Code Generation by Differential Test Time Scaling Multi-Step Likelihood-Ratio Correction for Reinforcement Learning with Verifiable Rewards A Sharper Picture of Generalization in Transformers NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding REFLECTOR: Internalizing Step-wise Reflection against Indirect Jailbreak Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics Divide et Calibra: Multiclass Local Calibration via Vector Quantization FBOS-RL: Feedback-Driven Bi-Objective Synergistic Reinforcement Learning Latent Process Generator Matching Design for Manufacturing: A Manufacturability Knowledge-Integrated Reinforcement Learning Framework for Free-Form Pipe Routing in Aeroengines Training Language Agents to Learn from Experience Tunable MAGMAX: Preference-Aware Model Merging for Continual Learning STELLAR: Scaling 3D Perception Large Models for Autonomous Driving CAdam: Context-Adaptive Moment Estimation for 3D Gaussian Densification in Generative Distillation Multi-agent Collaboration with State Management \ECUAS{n}: A family of metrics for principled evaluation of uncertainty-augmented systems From Circuit Evidence to Mechanistic Theory: An Inductive Logic Approach Behavior-Consistent Deep Reinforcement Learning torchtune: PyTorch native post-training library TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health OCTOPUS: Optimized KV Cache for Transformers via Octahedral Parametrization Under optimal Squared error quantization How Much Online RL is Enough? Informative Rollouts for Offline Preference Optimization in RLVR Data Scaling as Progressive Coverage of a Predictive Contribution Spectrum Instance Discrimination for Link Prediction SDM: A Powerful Tool for Evaluating Model Robustness Residual Paving: Diagnosing the Routing Bottleneck in Selective Refusal Editing Geometry-Lite: Interpretable Safety Probing via Layer-Wise Margin Geometry Improving Quantized Model Performance in Qualitative Analysis with Multi-Pass Prompt Verification Multi-Agent Reinforcement Learning for Safe Autonomous Driving Under Pedestrian Behavioral Uncertainty Approximation Theory for Neural Networks: Old and New ClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions Spectral Unforgetting: Post-Hoc Recovery of Damaged Capabilities Without Retraining Closed-form predictive coding via hierarchical Gaussian filters Modality-Decoupled Online Recursive Editing LLM Pretraining Shapes a Generalizable Manifold: Insights into Cross-Modal Transfer to Time Series Quant.npu: Enabling Efficient Mobile NPU Inference for on-device LLMs via Fully Static Quantization Hack-Verifiable Environments: Towards Evaluating Reward Hacking at Scale AgentAtlas: Beyond Outcome Leaderboards for LLM Agents Automated Kernel Discovery Towards Understanding High-dimensional Bayesian Optimization DEL: Digit Entropy Loss for Numerical Learning of Large Language Models AVSD: Adaptive-View Self-Distillation by Balancing Consensus and Teacher-Specific Privileged Signals Efficient Table QA via TableGrid Navigation and Progressive Inference Prompting Tippett-minimum Fusion of Representation-space Diffusion Models for Multi-Encoder Out-of-Distribution Detection Long-Context Reasoning Through Proxy-Based Chain-of-Thought Tuning HiRes: Inspectable Precedent Memory for Reaction Condition Recommendation

AOP-Wiki EMOD 3.0: Data Model Expansions and Content Evaluation Framework for Using Agentic AI to Improve Integration between AOPs and New Approach Methodologies (NAMs)

Virginia K. · 2026-05-23 · via cs.AI 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。