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Found 8 papers, 2 papers with code
Performance Evaluation of Large Language Models in Statistical Programming
This study offers valuable insights into the capabilities and limitations of LLMs in statistical programming, providing guidance for future advancements in AI-assisted coding systems for statistical analysis.
Enabling Autonomic Microservice Management through Self-Learning Agents
The increasing complexity of modern software systems necessitates robust autonomic self-management capabilities.
Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks
The rise of large language models (LLMs) has revolutionized user interactions with knowledge-based systems, enabling chatbots to synthesize vast amounts of information and assist with complex, exploratory tasks.
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
Large language model (LLM)-based AI delegates are increasingly utilized to act on behalf of users, assisting them with a wide range of tasks through conversational interfaces.
Turn Every Application into an Agent: Towards Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents
This framework also facilitates the creation and expansion of APIs through automated exploration of applications.
EfficientRAG: Efficient Retriever for Multi-Hop Question Answering
Retrieval-augmented generation (RAG) methods encounter difficulties when addressing complex questions like multi-hop queries.
The Vision of Autonomic Computing: Can LLMs Make It a Reality?
The Vision of Autonomic Computing (ACV), proposed over two decades ago, envisions computing systems that self-manage akin to biological organisms, adapting seamlessly to changing environments.
Towards Understanding Residual and Dilated Dense Neural Networks via Convolutional Sparse Coding
Inspired by these considerations, we propose two novel multi-layer models--residual convolutional sparse coding model (Res-CSC) and mixed-scale dense convolutional sparse coding model (MSD-CSC), which have close relationship with the residual neural network (ResNet) and mixed-scale (dilated) dense neural network (MSDNet), respectively.
