AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
1,707 papers
This work introduces REFINE (Refactoring with Evidence-aware Flow for Integrated ageNtic Execution), a tool-agnostic, evidence-aware multi-agent approach for generating Java file-level refactoring candidates that achieves a higher median code-smell reduction with smaller edits and fewer public-method removals.
The paper argues that algorithmic governance should not be assessed only by whether systems are accurate, explainable or compliant, but also by whether affected persons retain interpretive agency, contestatory power, relational recognition and meaningful participation in institutional life.
A simulator-grounded construction framework, instantiated as 3DTongueQA, that shows geometry-grounded supervision supporting both unified language QA and structured prediction and shows geometry-grounded supervision supporting both unified language QA and structured prediction.
This work presents FleetScape, a Mixed Reality (MR) sandtable system that externalizes layered real-time mission, safety, and environmental data while enabling fluid transitions between manual intervention and autonomous supervision and shows that FleetScape supports situational awareness through layered spatial repres...
Reach audiences
Advertise in front of researchers, engineers, and readers.
Visualization researchers utilize workshops both for applied research and to engage different populations with visualization‐based activities. While there are many benefits to running visualization workshops, their utility and impact rely on the presence of a researcher who has deep knowledge about visualization theo...
It is found that the MPA significantly influenced the PMPA and perceived virtue scores, and the best-fitting model to describe the relationship between PMPA and PVS was cubic, which is symmetrical in nature.
The SOPHIAS dataset, a 12-hour multimodal dataset containing recordings of 50 oral presentations delivered by 65 undergraduate and master's students at the Universidad Autonoma de Madrid, enables the exploration of relationships between multimodal behavioral and physiological signals and presentation performance, and p...
A bilingual survey of 199 participants in Bangladesh rated fairness across three everyday scenarios -- ride-sharing prices that shift with context, AI beauty filters that reshape appearance, and large language models that handle cultural values differently than a human would.
This paper uses 119 conversations with 100 or more participants and an extensive data export, drawn from a wider set of 271 collected processes, to ask what determines the output of such a process.
It is argued that AI sensemaking tools risk flattening the rich data patterns, amplifying contradictory textures of user feedback into sterile categories thereby transforming design research from an interpretive craft into a mechanical sorting exercise (rigid and formal).
The qualitative analysis reveals the factors users consider in their anchoring decision, including interface accessibility, stability during interaction, visual clutter, and individual mental models, which inform the design of adaptive and controllable MR interfaces and highlight the importance of supporting user custo...
It is demonstrated that standard LtD strategies show class-dependent sampling bias in classification tasks in practice, and thus may disproportionately defer the minority classes when applied to imbalanced datasets, and that such asymmetries in task delegation may trigger human biases, ultimately leading to poorer down...
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
A Blog post by H company on Hugging Face
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
