Papers by Liner Yang
On LLM-Based Scientific Inductive Reasoning Beyond Equations (2025.emnlp-main)
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Brian S. Lin, Jiaxin Yuan, Zihan Zhou, Shouli Wang, Shuo Wang, Cunliang Kong, Qi Shi, Yuxuan Li, Liner Yang, Zhiyuan Liu, Maosong Sun
| Challenge: | Existing research on inductive reasoning models emphasizes rule design without grounding them in specific scenarios. |
| Approach: | They propose to use LLMs to learn underlying patterns from limited examples in entirely new environments. |
| Outcome: | The proposed benchmark evaluates the inductive reasoning abilities of large language models in scientific settings. |
MCTS: A Multi-Reference Chinese Text Simplification Dataset (2024.lrec-main)
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Ruining Chong, Luming Lu, Liner Yang, Jinran Nie, Zhenghao Liu, Shuo Wang, Shuhan Zhou, Yaoxin Li, Erhong Yang
| Challenge: | Existing studies on text simplification systems have focused on unsupervised methods due to the limited evaluation data in language and domain. |
| Approach: | They propose a Chinese text simplification dataset that provides a detailed analysis and an annotation process. |
| Outcome: | The proposed dataset evaluates the performance of unsupervised methods and advanced large language models. |
Leveraging Prefix Transfer for Multi-Intent Text Revision (2023.acl-short)
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Ruining Chong, Cunliang Kong, Liu Wu, Zhenghao Liu, Ziye Jin, Liner Yang, Yange Fan, Hanghang Fan, Erhong Yang
| Challenge: | Text revision is a necessary process to improve text quality. |
| Approach: | They propose a multi-intent text revision system that can revise texts without explicit intent annotation. |
| Outcome: | The proposed system outperforms baselines on the IteraTeR dataset and significantly improves the SARI score with more than 3% improvement. |
Multitasking Framework for Unsupervised Simple Definition Generation (2022.acl-long)
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| Challenge: | Existing definition generation tasks require a dictionary with complex definitions and a corpus containing arbitrary simple texts to generate them. |
| Approach: | They propose a multitasking framework SimpDefiner that only requires a standard dictionary with complex definitions and a corpus containing arbitrary simple texts. |
| Outcome: | The proposed framework outperforms the baseline model by a 1.77 SARI score on the English dataset, and raises the proportion of the low level (HSK level 1-3) words in Chinese definitions by 3.87%. |
Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction (2021.naacl-main)
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| Challenge: | Existing GEC models produce spurious corrections or fail to detect lots of errors. |
| Approach: | They propose a neural network for GEC quality estimation with multiple hypotheses . VERNet establishes interactions among hypothese based on reasoning graph . |
| Outcome: | The proposed model achieves state-of-the-art grammatical error detection performance and best quality estimation results on four GEC datasets. |
UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset (2024.acl-long)
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Haoyu Wang, Shuo Wang, Yukun Yan, Xujia Wang, Zhiyu Yang, Yuzhuang Xu, Zhenghao Liu, Liner Yang, Ning Ding, Xu Han, Zhiyuan Liu, Maosong Sun
| Challenge: | Open-source large language models (LLMs) have gained strength across diverse fields, but the majority of studies focus on English. |
| Approach: | They propose a knowledge-grounded data augmentation approach to elicit more language-specific knowledge of LLMs by enhancing their ability to serve users from different countries. |
| Outcome: | The proposed method can prune the language-agnostic supervised fine-tuning dataset without any performance degradation. |
CTAP for Chinese:A Linguistic Complexity Feature Automatic Calculation Platform (2022.lrec-1)
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| Challenge: | Existing tools to analyze linguistic complexity are limited and different because of different research purposes. |
| Approach: | They propose to integrate Chinese component into CTAP to analyze linguistic complexity . they propose to use 196 linguistic complex indexes to calculate linguistic characteristics . |
| Outcome: | The proposed indexes are compared with three linguistic complexity tools for Chinese . the proposed index sets include four levels of 196 linguistic complex indexe . |