Papers by Xiaomin Li
Automated Chinese Essay Scoring from Multiple Traits (2022.coling-1)
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| Challenge: | Current research on AES focuses on scoring the overall quality or single trait of prompt-specific essays. |
| Approach: | They propose a hierarchical multi-task trait scorer to evaluate quality of writing . they propose an inter-sequence attention mechanism to enhance information interaction . |
| Outcome: | The proposed model outperforms several strong models on ACEA and outperformed other models. |
Chinese Paragraph-level Discourse Parsing with Global Backward and Local Reverse Reading (2020.coling-main)
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| Challenge: | Existing methods on discourse parsing in English suffer from long discourse units and fewer explicit connectives. |
| Approach: | They propose to use two reading modes to construct Chinese paragraph level discourse trees. |
| Outcome: | The proposed model outperforms baselines on Chinese discourse trees. |
Factual Relation Discrimination for Factuality-oriented Abstractive Summarization (2023.findings-emnlp)
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| Challenge: | Existing factuality-oriented abstractive summarization models only consider the integration of factual information and ignore the causes of factuual errors. |
| Approach: | They propose a factuality-oriented abstractive summarization model that can identify the causes of factual errors. |
| Outcome: | The proposed model outperforms state-of-the-art models in factual metrics. |
MCDTB: A Macro-level Chinese Discourse TreeBank (C18-1)
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| Challenge: | Discourse analysis is becoming increasingly important in the field of natural language processing. |
| Approach: | They propose to annotate macro discourse information and additional discourse information to make annotation more objective and accurate. |
| Outcome: | The results show that the annotations are more objective and accurate than the previous ones. |
Advancing Topic Segmentation and Outline Generation in Chinese Texts: The Paragraph-level Topic Representation, Corpus, and Benchmark (2024.lrec-main)
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| Challenge: | Compared with sentence-level topic structure, paragraph-level topics can grasp and understand the context of a document from a higher level. |
| Approach: | They propose a hierarchical paragraph-level topic structure representation with three layers to guide corpus construction. |
| Outcome: | The proposed method achieves the largest Chinese paragraph-level topic structure corpus, achieving high quality. |
Not Just Classification: Recognizing Implicit Discourse Relation on Joint Modeling of Classification and Generation (2021.emnlp-main)
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| Challenge: | Existing methods of implicit discourse relation recognition (IDRR) focus on three aspects: enhancing discourse units representation, enhancing semantic interaction, and joint learning with other tasks. |
| Approach: | They propose a joint model to recognize the relation label and generate the target sentence containing the meaning of relations simultaneously. |
| Outcome: | The proposed model achieves the best performance against several state-of-the-art systems on Chinese and English datasets. |
Seek-and-Solve: Benchmarking MLLMs for Visual Clue-Driven Reasoning in Daily Scenarios (2026.findings-acl)
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Xiaomin Li, Tala Wang, Zichen Zhong, Ying Zhang, Zirui Zheng, Takashi Isobe, Dezhuang Li, Huchuan Lu, You He, Xu Jia
| Challenge: | Existing benchmarks focus on evaluating MLLMs’ pre-existing knowledge or perceptual understanding, often neglecting the critical capability of reasoning. |
| Approach: | They propose a benchmark designed for visual clue-driven reasoning in daily scenarios that combines rigorous grounding in authentic daily activities and challenging query design that necessitates more than surface-level perception. |
| Outcome: | The proposed benchmark identifies visual clues and their ability to provide robust reasoning in daily scenarios. |