Search Results for author:
Found 8 papers, 2 papers with code
Generative AI to Generate Test Data Generators
The results show that LLMs can successfully generate realistic test data generators in a wide range of domains at all three levels of integrability.
RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
This results in RepairLLaMA producing a highly effective `program repair adapter' for fixing bugs with language models.
Supersonic: Learning to Generate Source Code Optimizations in C/C++
Software optimization refines programs for resource efficiency while preserving functionality.
Echotune: A Modular Extractor Leveraging the Variable-Length Nature of Speech in ASR Tasks
The Transformer architecture has proven to be highly effective for Automatic Speech Recognition (ASR) tasks, becoming a foundational component for a plethora of research in the domain.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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SignDiff: Learning Diffusion Models for American Sign Language Production
The field of Sign Language Production (SLP) lacked a large-scale, pre-trained model based on deep learning for continuous American Sign Language (ASL) production in the past decade.
UniBriVL: Robust Universal Representation and Generation of Audio Driven Diffusion Models
Multimodal large models have been recognized for their advantages in various performance and downstream tasks.
Exploring Efficient-Tuned Learning Audio Representation Method from BriVL
Recently, researchers have gradually realized that in some cases, the self-supervised pre-training on large-scale Internet data is better than that of high-quality/manually labeled data sets, and multimodal/large models are better than single or bimodal/small models.
Deep Smart Contract Intent Detection
Nowadays, security activities in smart contracts concentrate on vulnerability detection.
