Tong Wu
Tong Wu has 4 papers in our library, in 2025–2026, most of them on Word sense disambiguation, Language models & pretraining, Sentiment & emotion; often with Huizhi(elly) Liang, Deyi Xiong, Nicolay Rusnachenko.
OpenAlex · h-index 0 · 3 works · 0 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 19 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #8119
Affiliations
Fields, topics and concepts
📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 works
🧭 Topics 5Research subjects and languages the work is about.Bias, fairness & safety · 1 workLanguage models & pretraining · 1 workMultilingual & cross-lingual NLP · 1 workSentiment & emotion · 1 workWord sense disambiguation · 1 work
Works by year
2020s
Papers
- The Task Shield: Enforcing Task Alignment to Defend Against Indirect Prompt Injection in LLM Agents (2025 · 27 citations)
LLM agents that call tools can be hijacked by indirect prompt injection, where an attacker hides instructions in web pages, documents or tool outputs that the agent reads. - Automated Progressive Red Teaming (2025 · 10 citations)
Human red teaming of LLMs works but is slow and costly, and most automated attackers either stay frozen or never learn from the target model's feedback. - NCL-BU at SemEval-2026 Task 3: Fine-tuning XLM-RoBERTa for Multilingual Dimensional Sentiment Regression (2026 · 1 citation)
This paper reports a system for SemEval-2026 Task 3 (DimABSA), Track A, Subtask 1. In this subtask, each aspect mentioned in a sentence receives two continuous scores, valence and arousal, on a 1–9 scale, rather than a categorical polarity label. The authors fine-tune XLM-RoBERTa-base on input pairs of the form… - NCL-UoR at SemEval-2026 Task 5: Embedding-Based Methods, Fine-Tuning, and LLMs for Word Sense Plausibility Rating (2026 · 1 citation)
This SemEval-2026 Task 5 system paper tackles graded word sense plausibility. Given a five-sentence English story from the AmbiStory dataset with an ambiguous homonym and a candidate sense, a system must predict how plausible human annotators find that sense on a 1–5 scale. The authors compare three families of…
All works
- The Task Shield: Enforcing Task Alignment to Defend Against Indirect Prompt Injection in LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Feiran Jia, Tong Wu, Xin Qin, et al.2025 · 27 citations
- Automated Progressive Red TeamingInternational Conference on Computational Linguistics (COLING)Bojian Jiang, Yi Jing, Tong Wu, et al.2025 · 10 citations
- NCL-BU at SemEval-2026 Task 3: Fine-tuning XLM-RoBERTa for Multilingual Dimensional Sentiment RegressionInternational Workshop on Semantic Evaluation (SemEval)Tong Wu, Nicolay Rusnachenko, Huizhi(elly) Liang2026 · 1 citation
- NCL-UoR at SemEval-2026 Task 5: Embedding-Based Methods, Fine-Tuning, and LLMs for Word Sense Plausibility RatingInternational Workshop on Semantic Evaluation (SemEval)Tong Wu, Thanet Markchom, Huizhi(elly) Liang2026 · 1 citation
- Targeting the Needle, Ignoring the Haystack: Anchoring Crucial Cues for Evolving Scam Call Detection via an LLM-Assisted Classifier ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetTong Wu et al.2026
Co-authors here
Venues
- International Workshop on Semantic Evaluation (SemEval) ×2: SemEval 2026 ×2
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2025
- International Conference on Computational Linguistics (COLING): COLING 2025
- Findings of the Association for Computational Linguistics: ACL 2026
Cited by
Updated
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