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20232025
most citedImproving Seq2Seq Grammatical Error Correction via Decoding Interventions

3 citations · 4 across the 3 of their papers we have counts for

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cs.CL2024

DISC: Plug-and-Play Decoding Intervention with Similarity of Characters for Chinese Spelling Check

Ziheng Qiao, Houquan Zhou, Yumeng Liu +6

One key characteristic of the Chinese spelling check (CSC) task is that incorrect characters are usually similar to the correct ones in either phonetics or glyph. To accommodate th…

cs.CL2024

A Simple yet Effective Training-free Prompt-free Approach to Chinese Spelling Correction Based on Large Language Models

Houquan Zhou, Zhenghua Li, Bo Zhang +5

This work proposes a simple training-free prompt-free approach to leverage large language models (LLMs) for the Chinese spelling correction (CSC) task, which is totally different f…

cs.CL2024

SocialBench: Sociality Evaluation of Role-Playing Conversational Agents

Hongzhan Chen, Hehong Chen, Ming Yan +8

Large language models (LLMs) have advanced the development of various AI conversational agents, including role-playing conversational agents that mimic diverse characters and human…

cs.CL2024

Improving Cross-lingual Representation for Semantic Retrieval with Code-switching

Mieradilijiang Maimaiti, Yuanhang Zheng, Ji Zhang +3

Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario. The demands for a cross-lingual smart-cus…

cs.CL20233 cited

Improving Seq2Seq Grammatical Error Correction via Decoding Interventions

Houquan Zhou, Yumeng Liu, Zhenghua Li +5

The sequence-to-sequence (Seq2Seq) approach has recently been widely used in grammatical error correction (GEC) and shows promising performance. However, the Seq2Seq GEC approach s…