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Found 11 papers, 4 papers with code
Semantic Compression With Large Language Models
The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks.
ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design
This paper presents prompt design techniques for software engineering, in the form of patterns, to solve common problems when using large language models (LLMs), such as ChatGPT to automate common software engineering activities, such as ensuring code is decoupled from third-party libraries and simulating a web application API before it is implemented.
A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
This paper describes a catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs.
NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
First, we describe a state-of-the-art translation model used to generate Bash Commands from the corresponding English text.
Ranked #1 on
Code Translation
on NLC2CMD
Deep Learning Models on CPUs: A Methodology for Efficient Training
First, it presents a method for optimizing the training of deep learning models on Intel CPUs and a toolkit called ProfileDNN, which we developed to improve performance profiling.
A Transformer-based Approach for Translating Natural Language to Bash Commands
This paper explores the translation of natural language into Bash Commands, which developers commonly use to accomplish command-line tasks in a terminal.
Ranked #2 on
Code Translation
on NLC2CMD
Complementing Handcrafted Features with Raw Waveform Using a Light-weight Auxiliary Model
Instead of evaluating handcrafted features and raw waveforms independently, this paper proposes an Auxiliary Rawnet model to complement handcrafted features with features learned from raw waveforms.
FastAudio: A Learnable Audio Front-End for Spoof Speech Detection
The FastAudio front-end achieves a relative improvement of 27% when compared with fixed front-ends, outperforming all other learnable front-ends on this task.
Ranked #1 on
Voice Anti-spoofing
on ASVspoof2019
NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands
The NLC2CMD Competition hosted at NeurIPS 2020 aimed to bring the power of natural language processing to the command line.
Automated Diagnosis of Clinic Workflows
Outpatient clinics often run behind schedule due to patients who arrive late or appointments that run longer than expected.
DxNAT - Deep Neural Networks for Explaining Non-Recurring Traffic Congestion
We use data related to real-time traffic speed, jam factors (a traffic congestion indicator), and events collected over a year from Nashville, TN to train a multi-layered deep neural network.
