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        <title>When Less Is More: Logits-Constrained Framework with RoBERTa for Ancient Chinese NER</title>
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            <title>Proceedings of the Second Workshop on Ancient Language Processing</title>
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    <abstract>This report presents our team’s work on ancient Chinese Named Entity Recognition (NER) for EvaHan 20251. We propose a two-stage framework combining GujiRoBERTa with a Logits-Constrained (LC) mechanism. The first stage generates contextual embeddings using GujiRoBERTa, followed by dynamically masked decoding to enforce valid BMES transitions. Experiments on EvaHan 2025 datasets demonstrate the framework’s effectiveness. Key findings include the LC framework’s superiority over CRFs in high-label scenarios and the detrimental effect of BiLSTM modules. We also establish empirical model selection guidelines based on label complexity and dataset size.</abstract>
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%0 Conference Proceedings
%T When Less Is More: Logits-Constrained Framework with RoBERTa for Ancient Chinese NER
%A Hua, Wenjie
%A Xu, Shenghan
%Y Anderson, Adam
%Y Gordin, Shai
%Y Li, Bin
%Y Liu, Yudong
%Y Passarotti, Marco C.
%Y Sprugnoli, Rachele
%S Proceedings of the Second Workshop on Ancient Language Processing
%D 2025
%8 May
%I Association for Computational Linguistics
%C The Albuquerque Convention Center, Laguna
%@ 979-8-89176-235-0
%F hua-xu-2025-less
%X This report presents our team’s work on ancient Chinese Named Entity Recognition (NER) for EvaHan 20251. We propose a two-stage framework combining GujiRoBERTa with a Logits-Constrained (LC) mechanism. The first stage generates contextual embeddings using GujiRoBERTa, followed by dynamically masked decoding to enforce valid BMES transitions. Experiments on EvaHan 2025 datasets demonstrate the framework’s effectiveness. Key findings include the LC framework’s superiority over CRFs in high-label scenarios and the detrimental effect of BiLSTM modules. We also establish empirical model selection guidelines based on label complexity and dataset size.
%R 10.18653/v1/2025.alp-1.25
%U https://aclanthology.org/2025.alp-1.25/
%U https://doi.org/10.18653/v1/2025.alp-1.25
%P 192-196

Markdown (Informal)

[When Less Is More: Logits-Constrained Framework with RoBERTa for Ancient Chinese NER](https://aclanthology.org/2025.alp-1.25/) (Hua & Xu, ALP 2025)

• When Less Is More: Logits-Constrained Framework with RoBERTa for Ancient Chinese NER (Hua & Xu, ALP 2025)

ACL

• Wenjie Hua and Shenghan Xu. 2025. When Less Is More: Logits-Constrained Framework with RoBERTa for Ancient Chinese NER. In Proceedings of the Second Workshop on Ancient Language Processing, pages 192–196, The Albuquerque Convention Center, Laguna. Association for Computational Linguistics.