Federated few-shot learning for mobile nlp
Natural language processing (NLP) sees rich mobile applications. To support various
language understanding tasks, a foundation NLP model is often fine-tuned in a federated …
language understanding tasks, a foundation NLP model is often fine-tuned in a federated …
Multi-Task Domain Adaptation for Language Grounding with 3D Objects
The existing works on object-level language grounding with 3D objects mostly focus on
improving performance by utilizing the offthe-shelf pre-trained models to capture features …
improving performance by utilizing the offthe-shelf pre-trained models to capture features …
[PDF][PDF] Augmenting knowledge-based conversational search systems with large language models
M Klettner - 2024 - wwwmatthes.in.tum.de
Conversational interfaces are increasingly used by websites and apps, including office
software as well as creativity tools. This trend reflects a shift towards natural language in …
software as well as creativity tools. This trend reflects a shift towards natural language in …
[PDF][PDF] Federated nlp in few-shot scenarios
Natural language processing (NLP) sees rich mobile applications. To support various
language understanding tasks, a foundation NLP model is often fine-tuned in a federated …
language understanding tasks, a foundation NLP model is often fine-tuned in a federated …
The Role of Output Vocabulary in T2T LMs for SPARQL Semantic Parsing
In this work, we analyse the role of output vocabulary for text-to-text (T2T) models on the task
of SPARQL semantic parsing. We perform experiments within the the context of knowledge …
of SPARQL semantic parsing. We perform experiments within the the context of knowledge …
Memorization of Named Entities in Fine-Tuned BERT Models
Privacy preserving deep learning is an emerging field in machine learning that aims to
mitigate the privacy risks in the use of deep neural networks. One such risk is training data …
mitigate the privacy risks in the use of deep neural networks. One such risk is training data …
Review of Text Neural Semantic Parsing Methods
S Lingyun, L Xiaoqiu - Data Analysis and Knowledge …, 2024 - manu44.magtech.com.cn
[Objective] This paper summarizes and comments on the research methods of text semantic
parsing with neural networks in the past decade.[Coverage] With Google Scholar and CNKI …
parsing with neural networks in the past decade.[Coverage] With Google Scholar and CNKI …
Knowledge Graph Question Answering with Generative Language Models
D Banerjee - 2024 - search.proquest.com
Abstract A Knowledge Graph (KG) is a data structure that stores information about the world
in the form of nodes and edges. The nodes represent people, places, things etc., while the …
in the form of nodes and edges. The nodes represent people, places, things etc., while the …