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Found 5 papers, 1 papers with code
Generative AI for Software Metadata: Overview of the Information Retrieval in Software Engineering Track at FIRE 2023
The Information Retrieval in Software Engineering (IRSE) track aims to develop solutions for automated evaluation of code comments in a machine learning framework based on human and large language model generated labels.
Recovering from Privacy-Preserving Masking with Large Language Models
To effectively perform adaptation, textual data of users is typically stored on servers or their local devices, where downstream natural language processing (NLP) models can be directly trained using such in-domain data.
Language Agnostic Data-Driven Inverse Text Normalization
With the emergence of automatic speech recognition (ASR) models, converting the spoken form text (from ASR) to the written form is in urgent need.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Improving Data Driven Inverse Text Normalization using Data Augmentation
Inverse text normalization (ITN) is used to convert the spoken form output of an automatic speech recognition (ASR) system to a written form.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Database Workload Characterization with Query Plan Encoders
To address this workload characterization problem, we propose our query plan encoders that learn essential features and their correlations from query plans.
