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Found 11 papers, 2 papers with code
A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions
Research interest in autonomous agents is on the rise as an emerging topic.
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems A Case Study
In this paper, we introduce ML-On-Rails, a protocol designed to safeguard ML models, establish a well-defined endpoint interface for different ML tasks, and clear communication between ML providers and ML consumers (software engineers).
Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset
In this paper, we specifically focus on this underexplored context and conduct empirical analysis of LLMs (GPT-4 and GPT-3. 5) on question types, including single-choice, yes-no, multiple-choice, and number extraction questions from documents in zero-shot setting.
Smart Home Goal Feature Model -- A guide to support Smart Homes for Ageing in Place
Our model provides guidance to healthcare researchers and aged care industries to set up smart homes based on the needs of elderly, by defining a set of goals at different levels mapped to a different set of features.
Garbage in, garbage out: Zero-shot detection of crime using Large Language Models
This paper proposes exploiting the common sense knowledge learned by large language models to perform zero-shot reasoning about crimes given textual descriptions of surveillance videos.
Comparative analysis of real bugs in open-source Machine Learning projects -- A Registered Report
Objective: Our objective is to investigate whether there is a discrepancy in the distribution of resolution time between ML and non-ML issues and whether certain categories of ML issues require a longer time to resolve based on real issue reports in open-source applied ML projects.
SignalKG: Towards Reasoning about the Underlying Causes of Sensor Observations
This paper demonstrates our vision for knowledge graphs that assist machines to reason about the cause of signals observed by sensors.
Signal Knowledge Graph
This paper presents an knowledge graph to assist in reasoning over signals for intelligence purposes.
Beware the evolving 'intelligent' web service! An integration architecture tactic to guard AI-first components
Intelligent services provide the power of AI to developers via simple RESTful API endpoints, abstracting away many complexities of machine learning.
Interpreting Cloud Computer Vision Pain-Points: A Mining Study of Stack Overflow
The objective of this study is to determine the various pain-points developers face when implementing systems that rely on the most mature of these intelligent services, specifically those that provide computer vision.
Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
Multiple vendors now offer this technology as cloud services and developers want to leverage these advances to provide value to end-users.
