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Found 6 papers, 3 papers with code
Do Large Language Model Understand Multi-Intent Spoken Language ?
This research signifies a considerable breakthrough in leveraging Large Language Models (LLMs) for multi-intent spoken language understanding (SLU).
Mitigating Catastrophic Forgetting in Multi-domain Chinese Spelling Correction by Multi-stage Knowledge Transfer Framework
Chinese Spelling Correction (CSC) aims to detect and correct spelling errors in given sentences.
Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters
To the best of our knowledge, Visual-C$^3$ is the first real-world visual and the largest human-crafted dataset for the Chinese character checking scenario.
A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check
In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task in an end-to-end fashion.
On the (In)Effectiveness of Large Language Models for Chinese Text Correction
Recently, the development and progress of Large Language Models (LLMs) have amazed the entire Artificial Intelligence community.
Correct Like Humans: Progressive Learning Framework for Chinese Text Error Correction
During the training process, ProTEC guides the model to learn text error correction by incorporating these sub-tasks into a progressive paradigm.
