Papers by Zhiyuan Min

3 papers
AHVE-CNER: Aligned Hanzi Visual Encoding Enhance Chinese Named Entity Recognition with Multi-Information (2025.coling-main)

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Challenge: Existing glyph-based models neglect the relationship between pictorial elements and radicals for Named Entity Recognition (NER) tasks.
Approach: They propose a model that integrates multi-source visual and phonetic information of Hanzi . they propose combining pictographic features with radicals to facilitate integration .
Outcome: The proposed model improves performance on benchmark datasets.
Empowering Reliable Visual-Centric Instruction Following in MLLMs (2026.findings-acl)

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Challenge: Existing benchmarks for evaluating instruction-following capabilities focus on verbal instructions in the textual modality.
Approach: They propose to incorporate vision-dependent constraints into instruction design to enable a more rigorous assessment of how well MLLMs align their outputs with both visual input and textual instructions.
Outcome: The proposed benchmark incorporates vision-dependent constraints into instruction design, enabling a more rigorous and fine-grained assessment of how well MLLMs align their outputs with both visual input and textual instructions.
Progressive Self-Training with Discriminator for Aspect Term Extraction (2021.emnlp-main)

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Challenge: Existing approaches to extract aspect terms from review sentences are limited due to lack of annotated data.
Approach: They propose to refine conventional self-training to progressive self-teaching to reduce noise . they use a discriminator to filter the noisy pseudo-labels.
Outcome: The proposed model outperforms baseline models and achieves state-of-the-art performance on four SemEval datasets.

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