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Found 10 papers, 5 papers with code
Enhancing Chinese Pre-trained Language Model via Heterogeneous Linguistics Graph
Chinese pre-trained language models usually exploit contextual character information to learn representations, while ignoring the linguistics knowledge, e. g., word and sentence information.
LLMaAA: Making Large Language Models as Active Annotators
Recently, the superior few-shot performance of large language models (LLMs) has propelled the development of dataset generation, where the training data are solely synthesized from LLMs.
Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
Incorporating multiple knowledge sources is proven to be beneficial for answering complex factoid questions.
ADMUS: A Progressive Question Answering Framework Adaptable to Multiple Knowledge Sources
With the introduction of deep learning models, semantic parsingbased knowledge base question answering (KBQA) systems have achieved high performance in handling complex questions.
VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph
Semantic Web technology has successfully facilitated many RDF models with rich data representation methods.
gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpus
Furthermore, we also design a cloud-based self-adaptive task scheduling for gBuilder to ensure its scalability on large-scale knowledge graph construction.
RZCR: Zero-shot Character Recognition via Radical-based Reasoning
The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets.
Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge Base
Semantic parsing solves knowledge base (KB) question answering (KBQA) by composing a KB query, which generally involves node extraction (NE) and graph composition (GC) to detect and connect related nodes in a query.
FITAnnotator: A Flexible and Intelligent Text Annotation System
In this paper, we introduce FITAnnotator, a generic web-based tool for efficient text annotation.
Enhancing Pre-trained Chinese Character Representation with Word-aligned Attention
Most Chinese pre-trained models take character as the basic unit and learn representation according to character's external contexts, ignoring the semantics expressed in the word, which is the smallest meaningful utterance in Chinese.
