🧑‍🔬 Tianxing He

🏛️ Affiliations

🎓Tsinghua UniversityBeijing · China2024–2026 · 16 papersEmploymentcurrent🔬Shanghai Qi Zhi InstituteShanghai · China2024–2026 · 7 paperscurrent🎓Massachusetts Institute of TechnologyCambridge · United States2019–2023 · 15 papers🎓University of WashingtonSeattle · United States2022–2024 · 12 papers🎓Shanghai Jiao Tong UniversityShanghai · China2014–2023 · 9 papers🎓Johns Hopkins UniversityBaltimore · United States2023 · 2 papers🎓New York UniversityNew York · United States2021–2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

🧭 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. Can Language Models Solve Graph Problems in Natural Language? (2023 · 124 citations)
   Large language models are often applied to problems with hidden graph structure, such as robot planning, multi-hop QA and structured commonsense reasoning.
2. Resolving Knowledge Conflicts in Large Language Models (2023 · 48 citations)
   When LLMs receive retrieved or prompted text, that text often contradicts what they absorbed during pretraining.
3. Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models (2023 · 35 citations)
   Large language models are frozen after training and costly to update. As a result, they often produce outdated, hallucinated, or missing facts, especially for long-tail and fast-changing topics. Knowledge Card addresses this by attaching small, domain-specific language models ("knowledge cards") to a black-box LLM.…
4. Jailbreak Large Vision-Language Models Through Multi-Modal Linkage (2025 · 20 citations)
   This ACL 2025 paper studies why structure-based jailbreaks of large vision-language models (VLMs) succeed on open models such as LLaVA or MiniGPT-4 but largely fail on frontier systems like GPT-4o.
5. ChatAnime: Towards User-Centered Emotional Support in LLM-based Virtual Character Chat (2026)
   Users of virtual character platforms such as Character.AI increasingly seek emotional comfort from role-playing agents.

All works

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

1. Can Language Models Solve Graph Problems in Natural Language?Conference on Neural Information Processing Systems (NeurIPS)Heng Wang, Shangbin Feng, Tianxing He, et al.2023 · 124 citations
2. SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetAbe Hou et al.2024 · 77 citations
3. Negative Training for Neural Dialogue Response Generation ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetTianxing He, James Glass2020 · 77 citations
4. Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models ↗Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume · no summary yetTianxing He et al.2021 · 69 citations
5. Resolving Knowledge Conflicts in Large Language ModelsarXiv:2310.00935Yike Wang, Shangbin Feng, Heng Wang, et al.2023 · 48 citations
6. On the Blind Spots of Model-Based Evaluation Metrics for Text Generation ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetTianxing He et al.2023 · 46 citations
7. Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language ModelsarXiv:2305.09955Shangbin Feng, Weijia Shi, Yuyang Bai, et al.2023 · 35 citations
8. A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation ↗Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing · no summary yetMoin Nadeem et al.2020 · 29 citations
9. Jailbreak Large Vision-Language Models Through Multi-Modal LinkageAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Wang, Xiaofei Zhou, Yichen Wang, et al.2025 · 20 citations
10. Analyzing the Forgetting Problem in the Pretrain-Finetuning of Dialogue Response Models ↗arXiv (Cornell University) · no summary yetTianxing He et al.2019 · 19 citations
11. An Empirical Study on Few-shot Knowledge Probing for Pretrained Language Models ↗arXiv (Cornell University) · no summary yetTianxing He, Kyunghyun Cho, James Glass2021 · 9 citations
12. Controlling the Focus of Pretrained Language Generation Models ↗Findings of the Association for Computational Linguistics: ACL 2022 · no summary yetJiabao Ji et al.2022 · 3 citations
13. ChatAnime: Towards User-Centered Emotional Support in LLM-based Virtual Character ChatAnnual Meeting of the Association for Computational Linguistics (ACL)Lanlan Qiu, Sophia Xiao Pu, Yeqi Feng, et al.2026

🤝 Co-authors here

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

• Shangbin Feng ×3
• Yulia Tsvetkov ×3
• Heng Wang ×2
• Vidhisha Balachandran ×2
• Weijia Shi ×2
• Geyuan Zhang
• Xiaochuang Han
• Xiaofei Zhou
• Yichen Wang
• Yike Wang
• Yu Wang
• Zhaoxuan Tan

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) ×4: ACL 2026, ACL 2025
• Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2023
• Findings of the Association for Computational Linguistics: ACL 2022
• Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
• Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing
• Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

🔗 Cited by

Papers of our library cite their works 332 times (of the 149,439 papers whose bibliographies we read); 75 citing papers with a page here →.

Updated 2 November 2026

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