Papers by Xing Jia
From Coarse to Fine: A Multi-Granularity Multimodal Framework for Teacher Sentiment Analysis (2026.findings-acl)
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| Challenge: | Existing approaches to teacher sentiment analysis treat it as a static label . current approaches fail to capture structured heterogeneity of classroom expressions . |
| Approach: | They propose a coarse-to-fine multimodal framework that decomposes teacher sentiment into three granularities and employ CLS-guided cross-modal attention to recover effective signals from regulated displays. |
| Outcome: | The proposed framework outperforms state-of-the-art models on T-MED and CMU-MOSEI. |
Linking Adaptive Structure Induction and Neuron Filtering: A Spectral Perspective for Aspect-based Sentiment Analysis (2024.lrec-main)
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| Challenge: | incorporating structure information can improve the performance of aspect-based sentiment analysis. |
| Approach: | They propose a method to conduct neuron-level manipulations on word representations in the frequency domain. |
| Outcome: | The proposed method can achieve or come close to state-of-the-art in ABSA. |
MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training (2024.lrec-main)
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| Challenge: | Experimental evaluations conducted on the CMeEE, a benchmark for Chinese nested medical named entity recognition (NER) model outperforms the compared state-of-the-art (SOTA) models. |
| Approach: | They propose a model based on machine reading comprehension that uses a task-adaptive pre-training strategy to improve the model’s capability in the medical field. |
| Outcome: | The proposed model outperforms the compared state-of-the-art models on the CMeEE, a benchmark for Chinese nested medical NER. |