AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,069 papers
A Multi-Vocal Literature Review is conducted, combining insights from both academia and industry, including peer-reviewed studies and grey literature to systematically synthesize and analyze existing knowledge on LLM-based multi-agent systems for code generation.
This study provides the first large-scale empirical comparison of agentic frameworks for reasoning-intensive software engineering tasks and shows that framework selection should prioritize orchestration quality, especially memory control, failure handling, and cost management.
The vision is to leverage the capabilities of multiple GPT agents to contribute to SE tasks and to propose an initial road map for future work, arguing that multiple G PT agents can perform creative and demanding tasks far beyond coding and debugging.
This research highlights the heightened threats to data integrity and stakeholder trust in these evolving ecosystems through an intensive examination of the literature, initiating a pioneering discourse emphasizing fostering a foundation for developing secure and trustworthy Liquid AI environments.
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Carbon-Aware Governance Gates (CAGG), an architectural extension that embeds carbon budgets, energy provenance, and sustainability-aware validation orchestration into human-AI governance layers, is proposed.
Tree-based algorithms, such as XGBOOST – an open source implementation of Gradient Boosted Decision Trees (GBDT) – are ubiquitous for many Machine Learning (ML) tasks, especially when dealing with tabular/structured data and requir- ing explainability. As dataset size continues to grow, training ensembles of trees (ran...
Rapid urbanization has significantly increased pressure on transportation systems, healthcare, energy distribution, environmental monitoring, waste management, public safety, and other municipal services. Traditional city management approaches are increasingly unable to process the enormous volume of heterogeneous data...
Rapid urbanization has significantly increased pressure on transportation systems, healthcare, energy distribution, environmental monitoring, waste management, public safety, and other municipal services. Traditional city management approaches are increasingly unable to process the enormous volume of heterogeneous data...
Literature and practice has established that the lack of management commitment has been one of the top reasons for a failed SPI (software process improvement) initiative. The paper reports results from an ongoing study aimed at clarifying the role and the meaning of management commitment in SPI initiatives. Results fro...
It is shown that current thinking relies on models of commitment that are flawed in both academic and practical sense and four misconceptions are identified in current thinking.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
Education Innovation
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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