Papers by Junsheng Zhou
An Element-aware Multi-representation Model for Law Article Prediction (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing studies have shown that using law articles as external knowledge can improve the performance of the Legal Judgment Prediction. |
| Approach: | They propose a Law Article Element-aware Multi-representation Model which makes full use of law article information and can be used for multi-label samples. |
| Outcome: | The proposed model improves the accuracy of 5.84%, macro F1 of 6.42%, and micro F1 by 4.28% compared with baseline models like TopJudge. |
Event Detection as Graph Parsing (2021.findings-acl)
Copied to clipboard
| Challenge: | Existing approaches to event detection focus on using syntactic dependency structures or external knowledge to boost the performance. |
| Approach: | They propose a graph parsing problem that explicitly models multiple event correlations and utilizes rich information conveyed by event type and subtype. |
| Outcome: | The proposed model outperforms existing models on the public ACE2005 dataset by 4.2% on the dataset. |
NarGINA: Towards Accurate and Interpretable Children’s Narrative Ability Assessment via Narrative Graphs (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for assessing children's narrative ability are limited to evaluating completeness of narrative content and the coherence of expression, as well as interpretability of assessment results. |
| Approach: | They propose a computational framework for assessing narrative ability using a narrative graph to provide a concise and structured summary representation of narrative text. |
| Outcome: | The proposed framework achieves significant performance improvement over baselines while possessing good interpretability. |
Automated Essay Scoring via Pairwise Contrastive Regression (2022.coling-1)
Copied to clipboard
| Challenge: | Existing approaches to automate essay scoring use regression or ranking objectives . a novel neural pairwise ranking model is developed to optimize both objectives based on the same loss . |
| Approach: | They propose a novel Neural Pairwise Contrastive Regression model that optimizes both objectives simultaneously as a single loss. |
| Outcome: | The proposed model outperforms previous methods on the public Automated Student Assessment Prize dataset. |
Align-smatch: A Novel Evaluation Method for Chinese Abstract Meaning Representation Parsing based on Alignment of Concept and Relation (2022.lrec-1)
Copied to clipboard
| Challenge: | Abstract Meaning Representation abstracts the meaning of sentences into a single-rooted, acyclic and directed graph. |
| Approach: | They propose to use a metric to evaluate concept alignment and relation alignment to improve Chinese AMR parsing evaluation methods. |
| Outcome: | The proposed method is more robust and compatible with concept alignment and relation alignment and more robust in evaluating arcs. |