🧑‍🔬 Hao Tang

🏛️ Affiliations

🎓University of EdinburghEdinburgh · United Kingdom2021–2026 · 42 paperscurrent🎓Toyota Technological Institute at ChicagoChicago · United States2012–2017 · 11 papers🎓Massachusetts Institute of TechnologyCambridge · United States2018–2020 · 8 papers🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2018–2020 · 5 papers🎓Northwest UniversityXi'an · China2017–2018 · 2 papers🎓National Taiwan UniversityTaipei · Taiwan2009–2010 · 2 papers

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. Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification (2020 · 397 citations)
   The paper addresses aspect-based sentiment classification: deciding the polarity a sentence expresses toward a particular aspect, such as positive about "battery life" but negative about "memory" in the same review.
2. A framework for analyzing concept representations in neural models (2026)
   Interpretability work often assumes that human-interpretable concepts live in linear subspaces of a model's representation space.

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Tang, Donghong Ji, Chenliang Li, et al.2020 · 397 citations
2. Hierarchical Sketch Induction for Paraphrase Generation ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetTom Hosking, Hao Tang, Mirella Lapata2022 · 47 citations
3. A framework for analyzing concept representations in neural modelsConference on Computational Natural Language Learning (CoNLL)Burin Naowarat, Hao Tang, Sharon Goldwater2026
4. Learning Speech Representations with Variational Predictive Coding ↗Transactions of the Association for Computational Linguistics · no summary yetSung-Lin Yeh, Peter Bell, Hao Tang2026

🤝 Co-authors here

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

• Chenliang Li
• Donghong Ji
• Qiji Zhou
• Sharon Goldwater

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2020
• Conference on Computational Natural Language Learning (CoNLL): CoNLL 2026
• Transactions of the Association for Computational Linguistics

🔗 Cited by

Papers of our library cite their works 81 times (of the 141,840 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated 24 October 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/hao-tang/