Papers by Guanglu Sun
Learning or Self-aligning? Rethinking Instruction Fine-tuning (2024.acl-long)
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| Challenge: | Instruction fine-tuning (IFT) is a crucial phase in building large language models (LLMs). |
| Approach: | They propose a knowledge intervention framework to decouple the potential underlying factors of IFT and enable individual analysis of different factors. |
| Outcome: | The proposed framework decouples the potential underlying factors of IFT, enabling individual analysis of different factors. |
Dual-Stage Multi-Task Syntax-Oriented Pre-Training for Syntactically Controlled Paraphrase Generation (2024.findings-acl)
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| Challenge: | Syntactically controlled paraphrase generation (SCPG) aims to generate sentences with syntactic structures resembling given exemplars. |
| Approach: | They propose a dual-stage multi-task pre-training scheme that uses a series of structure-oriented and syntax-oriented tasks to generate sentences with syntactic structures resembling given exemplars. |
| Outcome: | The proposed method outperforms existing methods on all possible variants of SCPG tasks and significantly outperformed the popular T5 model. |
ESPVR: Entity Spans Position Visual Regions for Multimodal Named Entity Recognition (2023.findings-emnlp)
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| Challenge: | Existing methods for acquiring local visual information are limited . existing methods for named entity recognition are redundant or insufficient . |
| Approach: | They propose an Entity Spans Position Visual Regions module to obtain visual regions corresponding to entities in the text. |
| Outcome: | The proposed method achieves the SOTA on Twitter-2017 and competitive results on Twitter 2015 . previous efforts have yielded promising results, but they still fall short in selecting visual information. |
MPBoCo: Multimodal Prompt-based Boundary-enhanced Continual Framework for Joint Entity and Relation Extraction (2026.acl-long)
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| Challenge: | Existing methods struggle to balance real-time adaptability and computational efficiency in continual learning scenarios. |
| Approach: | They propose a Continual Multimodal Entity and Relation Joint Extraction task and a Multimodal Prompt-based Boundary-enhanced Continuum framework that stores task-specific knowledge via learnable multimodal prompts. |
| Outcome: | The proposed framework outperforms baseline methods in real-world scenarios by 5.5% and 7.2%. |
Ambiguous Learning from Retrieval: Towards Zero-shot Semantic Parsing (2023.acl-long)
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Shan Wu, Chunlei Xin, Hongyu Lin, Xianpei Han, Cao Liu, Jiansong Chen, Fan Yang, Guanglu Wan, Le Sun
| Challenge: | Existing neural semantic parsers require a large amount of training data which is expensive and difficult to obtain. |
| Approach: | They propose a framework for a supervised retrieval system based on pretrained language models . they propose ambiguous supervision to improve the precision and coverage of the task . |
| Outcome: | The proposed approach outperforms state-of-the-art zero-shot parsing methods in ambiguous supervision. |