Titlebook: Natural Language Processing and Chinese Computing; 13th National CCF Co Derek F. Wong,Zhongyu Wei,Muyun Yang Conference proceedings 2025 Th

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Enhancing Word-Level Completion for Masked Language Model with Multi-Model Fusionrocess of human translation and ensure the translation quality. Although significant progress has been made in the field, there may be multiple candidate words when models predict words. Multiple words make up a list of candidate words. We improve the existing model by determining the most credible

肥料

JumpLiteGCN: A Lightweight Approach to Hierarchical Text Classificationsification methods often face dual constraints of efficiency and performance. To overcome these challenges, this study proposes a lightweight graph convolutional network model enhanced with jump connections (JumpLiteGCN). This significantly reduces the model’s complexity and computational costs by s

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Enhancing Complex Causality Extraction via Improved Subtask Interaction and Knowledge Fusionthe best approach for the ECE task. However, existing fine-tuning based ECE methods cannot address all three key challenges in ECE simultaneously: 1) ., where multiple causal-effect pairs occur within a single sentence; 2) ., which involves modeling the mutual dependence between the two subtasks of

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Mathematical Reasoning via Multi-step Self Questioning and Answering for Small Language Modelsting works have tried to leverage the rationales of LLMs to train small language models (SLMs) for enhanced reasoning abilities, referred to as distillation. However, most existing distillation methods have not considered guiding the small models to solve problems progressively from simple to comple

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Modeling Comparative Logical Relation with Contrastive Learning for Text Generation a table. Existing D2T works mainly focus on describing the superficial . among entities, while ignoring the deep ., such as A is better than B in a certain aspect with a corresponding opinion, which is quite common in our daily life. In this paper, we introduce a new D2T task named comparative logi

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MANet: A Multiview Attention Network for Automatic ICD Codingrbose nature of medical records. Currently, most methods employ deep neural networks to learn the representation of clinical notes from a single perspective. These single-view-based methods overlook the exploitation and fusion of multiview features to enhance the precision of ICD coding. In this pap