Papers by Zijie Zeng
To Judge or Not to Judge: Can Large Language Models Leverage the Dispute Focus in Legal Judgment? (2026.acl-long)
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| Challenge: | Existing research on large language models for legal judgment prediction fails to address the complexity of civil judicial cases. |
| Approach: | They propose a framework that leverages the dispute focus to guide LLMs through a structured, judge-like cognitive workflow. |
| Outcome: | The proposed framework can guide LLMs through a structured, judge-like cognitive workflow. |
Do Deep Neural Nets Display Human-like Attention in Short Answer Scoring? (2022.naacl-main)
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| Challenge: | DL-based graders often lack the ability to explain and justify how a prediction is made, which decreases their trustworthiness and hinders educators from embracing them in practice. |
| Approach: | They conducted a user study to determine whether DL-based graders align with human grader . they also ran a randomized controlled experiment to explore the impact of highlighting important words detected by DL grader. |
| Outcome: | The proposed method enables human graders to identify important words when marking short answer questions. |
SEMIROUTER: Sparse-Data Enhanced Routing for Adaptive Multi-LLM System (2026.eacl-long)
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| Challenge: | Existing routing methods suffer from poor scalability and dependence on datasets for training . energy footprint is also considered in the decision to implement our new LLM routing framework . |
| Approach: | They propose a new LLM routing framework that dynamically allocates queries to the most appropriate LLM. |
| Outcome: | The proposed method improves data efficiency, adaptability, and routing accuracy compared to existing methods. |
CMNEE:A Large-Scale Document-Level Event Extraction Dataset Based on Open-Source Chinese Military News (2024.lrec-main)
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| Challenge: | Current research focuses on the general news or financial domains, with relatively few studies for military domain. |
| Approach: | They propose to annotate Chinese military news events from documents using a schema for the military domain. |
| Outcome: | The proposed dataset is large-scale, document-level open-source for the military domain . it contains 17,000 documents and 29,223 events, which are all manually annotated . |