@inproceedings{xie-huang-2026-ground,
title = "Ground Before Correcting: Evidence-Guided Visual {C}hinese Grammatical Error Correction at Multi-{LLL} 2026",
author = "Xie, Xiaochuan and
Huang, Keran",
editor = "Wang, Xiaoman and
Wang, Qianyu and
Liu, Zhengyuan and
Chen, Nancy F. and
Yuan, Zheng and
Lan, Yunshi and
Jiang, Jing",
booktitle = "Proceedings of the 1st Workshop on Multi-modality and Multi-lingual Language Learning",
month = nov,
year = "2026",
address = "Hengqin, Zhuhai, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.multilll-1.3/",
pages = "33--46",
ISBN = "979-8-89176-449-1",
abstract = "We describe the GroundCorrect system of team xc-皮波 for the Sentence-Level Track of VisCGEC-v2.0 at Multi-LLL 2026. The system combines frozen Qwen3-VL-4B-Instruct global recognition, rank-8 LoRA verification of full-line and local-crop evidence, and YOLO11s character detection with deterministic edit grounding. According to the retained team record, the official V3 competition submission ranked second with score 0.5114. This result belongs exclusively to the official submission, not to the local reconstruction or the post-submission V3+ extension. Our primary local adapter comparison holds inputs, prompt, decoding, and grounding fixed: the development proxy rises from 0.1254 to 0.2234. Other configuration changes are reported as system development. V3+ is an exploratory case study that changes one development example, with no internal-selection or grounded-edit improvement. Local results are conditional configuration analyses: selection images also train the detector, and development data overlap training at the essay-group level."
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%0 Conference Proceedings
%T Ground Before Correcting: Evidence-Guided Visual Chinese Grammatical Error Correction at Multi-LLL 2026
%A Xie, Xiaochuan
%A Huang, Keran
%Y Wang, Xiaoman
%Y Wang, Qianyu
%Y Liu, Zhengyuan
%Y Chen, Nancy F.
%Y Yuan, Zheng
%Y Lan, Yunshi
%Y Jiang, Jing
%S Proceedings of the 1st Workshop on Multi-modality and Multi-lingual Language Learning
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, Zhuhai, China
%@ 979-8-89176-449-1
%F xie-huang-2026-ground
%X We describe the GroundCorrect system of team xc-皮波 for the Sentence-Level Track of VisCGEC-v2.0 at Multi-LLL 2026. The system combines frozen Qwen3-VL-4B-Instruct global recognition, rank-8 LoRA verification of full-line and local-crop evidence, and YOLO11s character detection with deterministic edit grounding. According to the retained team record, the official V3 competition submission ranked second with score 0.5114. This result belongs exclusively to the official submission, not to the local reconstruction or the post-submission V3+ extension. Our primary local adapter comparison holds inputs, prompt, decoding, and grounding fixed: the development proxy rises from 0.1254 to 0.2234. Other configuration changes are reported as system development. V3+ is an exploratory case study that changes one development example, with no internal-selection or grounded-edit improvement. Local results are conditional configuration analyses: selection images also train the detector, and development data overlap training at the essay-group level.
%U https://aclanthology.org/2026.multilll-1.3/
%P 33-46
Markdown (Informal)
[Ground Before Correcting: Evidence-Guided Visual Chinese Grammatical Error Correction at Multi-LLL 2026](https://aclanthology.org/2026.multilll-1.3/) (Xie & Huang, Multi-LLL 2026)
ACL