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Found 9 papers, 3 papers with code
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction
The meaning of a word in Chinese is different in that a word is a compositional unit consisting of multiple characters.
Inferflow: an Efficient and Highly Configurable Inference Engine for Large Language Models
We present Inferflow, an efficient and highly configurable inference engine for large language models (LLMs).
RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation
In this paper, we introduce RobustGEC, a benchmark designed to evaluate the context robustness of GEC systems.
Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit hallucinations: LLMs occasionally generate content that diverges from the user input, contradicts previously generated context, or misaligns with established world knowledge.
Effidit: Your AI Writing Assistant
In Effidit, we significantly expand the capacities of a writing assistant by providing functions in five categories: text completion, error checking, text polishing, keywords to sentences (K2S), and cloud input methods (cloud IME).
Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errors
We achieve this by introducing a special token \texttt{[null]}, the prediction of which stands for the non-existence of a word.
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction
The meaning of a word in Chinese is different in that a word is a compositional unit consisting of multiple characters.
TexSmart: A System for Enhanced Natural Language Understanding
This paper introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
