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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.

4 papers in our library · 2025–2026

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

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. 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.
  2. 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.
  3. 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…
  4. 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

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. 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

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 19 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

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