Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
One SPRING to rule them both: Symmetric AMR semantic parsing and generation without a complex pipeline
In Text-to-AMR parsing, current state-of-the-art semantic parsers use cumbersome pipelines
integrating several different modules or components, and exploit graph recategorization, ie …
integrating several different modules or components, and exploit graph recategorization, ie …
Improving AMR parsing with sequence-to-sequence pre-training
In the literature, the research on abstract meaning representation (AMR) parsing is much
restricted by the size of human-curated dataset which is critical to build an AMR parser with …
restricted by the size of human-curated dataset which is critical to build an AMR parser with …
Modeling graph structure in transformer for better AMR-to-text generation
Recent studies on AMR-to-text generation often formalize the task as a sequence-to-
sequence (seq2seq) learning problem by converting an Abstract Meaning Representation …
sequence (seq2seq) learning problem by converting an Abstract Meaning Representation …
XL-AMR: Enabling cross-lingual AMR parsing with transfer learning techniques
Meaning Representation (AMR) is a popular formalism of natural language that represents
the meaning of a sentence as a semantic graph. It is agnostic about how to derive meanings …
the meaning of a sentence as a semantic graph. It is agnostic about how to derive meanings …
Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing
Predicting linearized Abstract Meaning Representation (AMR) graphs using pre-trained
sequence-to-sequence Transformer models has recently led to large improvements on AMR …
sequence-to-sequence Transformer models has recently led to large improvements on AMR …
End-to-end AMR coreference resolution
Abstract Although parsing to Abstract Meaning Representation (AMR) has become very
popular and AMR has been shown effective on the many sentence-level downstream tasks …
popular and AMR has been shown effective on the many sentence-level downstream tasks …
Hierarchical information matters! Improving AMR parsing with multi-granularity representation interactions
Meaning Representation (AMR) parsing aims to automatically translate text into a directed
and acyclic semantic graph, which recently has been improved significantly by Transformer …
and acyclic semantic graph, which recently has been improved significantly by Transformer …
SGL: Speaking the graph languages of semantic parsing via multilingual translation
Graph-based semantic parsing aims to represent textual meaning through directed graphs.
As one of the most promising general-purpose meaning representations, these structures …
As one of the most promising general-purpose meaning representations, these structures …
ParaAMR: A large-scale syntactically diverse paraphrase dataset by AMR back-translation
Paraphrase generation is a long-standing task in natural language processing (NLP).
Supervised paraphrase generation models, which rely on human-annotated paraphrase …
Supervised paraphrase generation models, which rely on human-annotated paraphrase …
Multilingual AMR parsing with noisy knowledge distillation
We study multilingual AMR parsing from the perspective of knowledge distillation, where the
aim is to learn and improve a multilingual AMR parser by using an existing English parser as …
aim is to learn and improve a multilingual AMR parser by using an existing English parser as …