惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园_首页
J
Java Code Geeks
IT之家
IT之家
Last Week in AI
Last Week in AI
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
B
Blog RSS Feed
P
Proofpoint News Feed
博客园 - Franky
MongoDB | Blog
MongoDB | Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
博客园 - 【当耐特】
Microsoft Security Blog
Microsoft Security Blog
I
InfoQ
B
Blog
Stack Overflow Blog
Stack Overflow Blog
Martin Fowler
Martin Fowler
博客园 - 聂微东
Y
Y Combinator Blog
Recent Announcements
Recent Announcements
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Apple Machine Learning Research
Apple Machine Learning Research
大猫的无限游戏
大猫的无限游戏
U
Unit 42
aimingoo的专栏
aimingoo的专栏

cs updates on arXiv.org

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment Agentic Proving for Program Verification MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts Solving the Aircraft Disassembly Scheduling Problem Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction Naturalistic measure of social norms alignment Articulatory strategy as a source of variation in acoustic vowel dynamics When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning Cultural Adaptation in Large Language Models for Political Discourse Emotion Recognition in Sign Language Conversation ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication AraHopeCorpus: Annotation Guidelines and Dataset for Hope Speech in Arabic Social Media Crisis Discourse Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning DART: Semantic Recoverability for Structured Tool Agents Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Parallel Context Compaction for Long-Horizon LLM Agent Serving
HPC-Enabled Generator Importance Assessment for RTO-Scale...
[Submitted on 12 Jun 2026] · 2026-06-15 · via cs updates on arXiv.org

View PDF

Abstract:Modern power systems are increasingly under stress as aging assets approach retirement and load growth outpaces new generation construction. The severity of this challenge varies by region: in the EU, the transmission grid can partially compensate for local generation shortfalls, while in the US, generation tends to be more localized, making retirements harder to offset. Retirement of generation has consequences for system reserves, fuel supply chain, and public health. We present an high-performance computing (HPC) framework for rapidly assessing the grid importance of individual generating units and ranking them by primary fuel type, operating cost, or grid impact. Historically, such studies were computationally intensive and therefore conducted infrequently. This work demonstrates that such assessments can be completed in minutes, enabling planners to evaluate a much broader range of generation portfolio scenarios than was previously possible.

Submission history

From: Slaven Peles [view email]
[v1] Fri, 12 Jun 2026 03:19:55 UTC (496 KB)