Shouling Ji
Shouling Ji has 3 papers in our library, in 2018–2026, most of them on Language models & pretraining, Bias, fairness & safety, Vision & language; often with Tianyu Du, Changjiang Li, Chunyi Zhou.
OpenAlex · ORCID · Wikidata · h-index 49 · 441 works · 8,160 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 245 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #3666
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 worksHardware and Architecture · 1 workComputer Vision and Pattern Recognition · 1 work
🧭 Topics 3Research subjects and languages the work is about.Bias, fairness & safety · 1 workLanguage models & pretraining · 1 workVision & language · 1 work
Works by year
2020s
2010s
Papers
- TextBugger: Generating Adversarial Text Against Real-world Applications (2018 · 545 citations)
The paper asks how fragile deep-learning text classifiers are, both research models and commercial cloud services, when an attacker makes small, human-readable edits to the input. - Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors (2026 · 1 citation)
The paper looks at supply-chain backdoors in safety-aligned LLMs. In this setting, an attacker with write access to a checkpoint wants a hidden trigger to unlock harmful answers, while the model behaves normally otherwise. Earlier weight-editing attacks such as JailbreakEdit train the model to open with an agreeing… - “I See What You Did There”: Can Large Vision-Language Models Understand Multimodal Puns? (2026 · 1 citation)
The paper asks whether vision-language models (VLMs) actually understand multimodal puns or only react to playful-looking content.
All works
- TextBugger: Generating Adversarial Text Against Real-world ApplicationsarXiv:1812.05271Jinfeng Li, Shouling Ji, Tianyu Du, et al.2018 · 545 citations
- Dual Encoding for Zero-Example Video Retrieval ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetJianfeng Dong et al.2019 · 304 citations
- Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models ↗Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · no summary yetJialuo Chen et al.2022 · 97 citations
- Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetHanlu Wu et al.2020 · 68 citations
- Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy BackdoorsAnnual Meeting of the Association for Computational Linguistics (ACL)Rui Yin, Tianxu Han, Naen Xu, et al.2026 · 1 citation
- “I See What You Did There”: Can Large Vision-Language Models Understand Multimodal Puns?Annual Meeting of the Association for Computational Linguistics (ACL)Naen Xu, Jiayi Sheng, Changjiang Li, et al.2026 · 1 citation
- StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetHuawei Zheng et al.2026
Co-authors here
- Tianyu Du ×3
- Changjiang Li ×2
- Chunyi Zhou ×2
- Jinbao Li ×2
- Jun Wang ×2
- Naen Xu ×2
- Zhihui Fu ×2
- Bo Li
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026 ×2
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
- Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Cited by
Updated
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