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

J
Java Code Geeks
腾讯CDC
Jina AI
Jina AI
博客园 - 司徒正美
博客园 - 三生石上(FineUI控件)
Apple Machine Learning Research
Apple Machine Learning Research
GbyAI
GbyAI
WordPress大学
WordPress大学
Hugging Face - Blog
Hugging Face - Blog
T
The Blog of Author Tim Ferriss
小众软件
小众软件
M
MIT News - Artificial intelligence
MyScale Blog
MyScale Blog
D
Docker
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Google DeepMind News
Google DeepMind News
月光博客
月光博客
L
LangChain Blog
F
Fortinet All Blogs
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - Franky
C
Check Point Blog
U
Unit 42
人人都是产品经理
人人都是产品经理

cs.SE updates on arXiv.org

VLA Foundry: A Unified Framework for Training Vision-Language-Action Models Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection Do Agents Dream of Root Shells? Partial-Credit Evaluation of LLM Agents in Capture the Flag Challenges Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning LLMSniffer: Detecting LLM-Generated Code via GraphCodeBERT and Supervised Contrastive Learning Neurosymbolic Repo-level Code Localization CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Verification Modulo Tested Library Contracts The Semi-Executable Stack: Agentic Software Engineering and the Expanding Scope of SE Scaling Test-Time Compute for Agentic Coding AI-Assisted Requirements Engineering: An Empirical Evaluation Relative to Expert Judgment From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution Atropos: Improving Cost-Benefit Trade-off of LLM-based Agents under Self-Consistency with Early Termination and Model Hotswap Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-Codex Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution AIPC: Agent-Based Automation for AI Model Deployment with Qualcomm AI Runtime Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks Asking What Matters: Reward-Driven Clarification for Software Engineering Tasks Prompt-Driven Code Summarization: A Systematic Literature Review LinuxArena: A Control Setting for AI Agents in Live Production Software Environments LLMs taking shortcuts in test generation: A study with SAP HANA and LevelDB Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends CollabCoder: Plan-Code Co-Evolution via Collaborative Decision-Making for Efficient Code Generation Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go? Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment
Enabling Context-awareness by Predicate Detection in Asyn...
Yiling Yang, Yu Huang, Xiaoxing Ma, Jian Lu · 2013-10-14 · via cs.SE updates on arXiv.org

Pervasive applications are involving more and more autonomous computing and communicating devices, augmented with the abilities of sensing and controlling the logical / physical environment. To enable context-awareness for such applications, we are challenged by the intrinsic asynchrony among the context collecting devices. To this end, we introduce the predicate detection theory and propose the Predicate-Detection-based Context-Awareness (PD-CA) framework, in which: a) logical time is used to explicitly cope with the asynchrony; b) specification of predicates enables the applications to express contextual properties of their concerns; c) online and incremental predicate detection algorithms effectively enable context-awareness at runtime. Under the guidance of the PD-CA framework, we present the design and implementation of the MIPA middleware, which shields the applications from the burden of processing the asynchronous contexts. We also demonstrate how PD-CA simplifies the development of context-aware applications. Experimental evaluations show the performance of MIPA in supporting context-aware applications despite of the asynchrony.