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Semantic code search, retrieving code that matches a given natural language query, is an important task to improve productivity in software engineering. Existing code search datasets face limitations: they rely on human annotators who assess code primarily through semantic understanding rather than functional verification, leading to potential inaccuracies and scalability issues. Additionally, current evaluation metrics often overlook the multi-choice nature of code search. This paper introduces CoSQA+, pairing high-quality queries from CoSQA with multiple suitable codes.
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This dataset comprises 30 CSV files featuring text-based narratives developed as part of the MOVING (MOuntain Valorisation through INterconnectedness and Green Growth) Horizon 2020 project, which explores 454 value chains across 23 rural regions in 16 European countries. Additionally, it includes 30 JSON files that annotate the keywords within these narratives, linking them to their corresponding Wikidata entries and QIDs.
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54 Views
This dataset comprises 30 CSV files featuring text-based narratives developed as part of the MOVING (MOuntain Valorisation through INterconnectedness and Green Growth) Horizon 2020 project, which explores 454 value chains across 23 rural regions in 16 European countries. Additionally, it includes 30 JSON files that annotate the keywords within these narratives, linking them to their corresponding Wikidata entries and QIDs.
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12 Views
Recent research indicates that fine-tuning smaller parameter language models using reasoning samples generated by large languages models (LLMs) can effectively enhance the performance of small models in complex reasoning tasks. However, after fine-tuning the small model using the existing Zero-shot-CoT method, there are still shortcomings in problem understanding, mathematical calculations, logical reasoning, and missing steps when handling problems.
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60 Views
With multiple large open source datasets, the development of action recognition is rapid. However, we noticed the lack of annotated data of cilvil aircraft pilots, while distribution of whose action can be very different from daily casual activities. After discussion with experienced pilots and experts and close look into standard operation procedure, we present Airline-Pilot-Action (APA) benchmark, containing 5090 RGB and depth images together with corresponding flight computer data.
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212 Views
M. Kacmajor and J.D. Kelleher, "ExTra: Evaluation of Automatically Generated Source Code Using Execution Traces" (submitted to IEEE TSE)
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M. Kacmajor and J.D. Kelleher, "ExTra: Evaluation of Automatically Generated Source Code Using Execution Traces" (submitted to IEEE TSE)
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The JKU-ITS AVDM contains data from 17 participants performing different tasks with various levels of distraction.
The data collection was carried out in accordance with the relevant guidelines and regulations and informed consent was obtained from all participants.
The dataset was collected using the JKU-ITS research vehicle with automated capabilities under different illumination and weather conditions along a secure test route within the
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960 Views
Nasal Cytology, or Rhinology, is the subfield of otolaryngology, focused on the microscope observation of samples of the nasal mucosa, aimed to recognize cells of different types, to spot and diagnose ongoing pathologies. Such methodology can claim good accuracy in diagnosing rhinitis and infections, being very cheap and accessible without any instrument more complex than a microscope, even optical ones.
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855 Views
Dataset for validation of a new magnetic field-based wearable breathing sensor (MAG), which uses the movement of the chest wall as a surrogate measure of respiratory activity. Based on the principle of variation in magnetic field strength with the distance from the source, this system explores Hall effect sensing, paired with a permanent magnet, embedded in a chest strap.
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532 Views