AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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20,463 papers
Tool-augmented LLM agents discover relevant APIs from large registries before planning execution, yet finite context windows prohibit injecting all tool definitions into a single prompt. The dominant approach, which we term Retrieve-then-Plan (RtP), embeds the user query and retrieves similar tools via approximate near...
Prompting is a widely used method for adapting general-purpose LLMs to domain-specific tasks. Effective prompts can be tedious to create manually, so prompt writing is increasingly handed to LLMs, with recent work training LLMs to write prompts for other models. These techniques either write prompts without observing h...
LLM agent frameworks heavily rely on external skill assets to standardize tool usage, encode operational workflows, and supply executable runtime resources. Despite their widespread adoption, multi-component skill packages frequently suffer from cross-artifact inconsistencies, where documentation, scripts, and configur...
Due to their complex and multifaceted character, liver diseases represent a huge global health burden and contribute considerably to morbidity and mortality globally. Although the liver is essential for detoxification, protein synthesis, metabolic equilibrium, and biochemical regulation, it is extremely vulnerable to d...
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Microbial infections continue to pose a significant global health challenge due to the increasing prevalence of antimicrobial resistance (AMR), multidrug-resistant (MDR) pathogens, and the limited effectiveness of conventional antimicrobial therapies. Traditional antimicrobial agents often suffer from poor aqueous solu...
Genotoxic impurities (GTIs) are trace-level contaminants capable of damaging DNA and increasing the potential for mutation and carcinogenesis. They may arise from starting materials, reagents, catalysts, intermediates, by-products, degradation pathways, manufacturing operations, or packaging interactions. Their control...
As artificial intelligence (AI) reshapes higher education, learning support centers are uniquely positioned to intentionally assess whether if and how to best integrate AI tools into academic services. This session presents a 6-week project framework that was designed to: • Review the literature on critical AI literacy...
As artificial intelligence reshapes virtually every field, universities face a growing imperative to ensure AI literacy is not reserved for computer science majors alone. This panel presents the collaborative design of an introductory AI course built for undergraduate general education — one that serves students across...
Artificial intelligence is increasingly used by students as a learning resource in STEM courses. However, classroom observations and survey data suggest that unstructured AI use may correlate with reduced student achievement. Two concerns are especially relevant: AI systems can produce incorrect responses in tasks requ...
The rapid integration of generative artificial intelligence into academic spaces requires a shift from passive restriction to resilient, active pedagogical frameworks. This virtual panel explores actionable strategies to protect academic integrity, promote deep critical thinking, and manage AI use, particularly in foun...
As artificial intelligence becomes increasingly integrated into higher education, it presents new opportunities to enhance the accessibility of instructional materials. This session examines how Microsoft Copilot, Adobe AI, and built-in Windows 11 features such as live auto-captions can support more accessible content...
Mental health assessment requires students to navigate complex conversations involving depression, anxiety, mania, psychosis, suicide risk, and other sensitive clinical situations. Yet opportunities to repeatedly practice these conversations in a safe, low-stakes environment can be limited. This session demonstrates an...
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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