Yulin Hu
Yulin Hu has 4 papers in our library, in 2025–2026, most of them on Bias, fairness & safety, Language models & pretraining, Sentiment & emotion; often with Bing Qin, Jiahe Guo, Weixiang Zhao.
OpenAlex · ORCID · Wikidata · h-index 33 · 272 works · 3,526 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 26 times in our library · ⭐ Paper Stars ranking: #9762
Affiliations
Fields, topics and concepts
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 worksSafety Research · 1 workSocial Sciences · 1 workExperimental and Cognitive Psychology · 1 workPsychology · 1 work
🧭 Topics 5Research subjects and languages the work is about.Bias, fairness & safety · 3 worksLanguage models & pretraining · 2 worksMultilingual & cross-lingual NLP · 1 workDialogue systems · 1 workSentiment & emotion · 1 work
Works by year
2020s
Papers
- AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak Defender (2025 · 11 citations)
Safety-aligned LLMs can still be jailbroken. Activation steering is a training-free defense that pushes hidden states toward refusal, but it applies one fixed strength to every input. That fixed setting under-protects against some attacks and causes more false refusals of harmless requests. AdaSteer makes the… - Beware of Your Po! Measuring and Mitigating AI Safety Risks in Role-Play Fine-Tuning of LLMs (2025 · 9 citations)
The paper examines how fine-tuning LLMs for character role-play affects their safety. The authors fine-tuned LLaMA-3-8B-Instruct separately for each of 95 characters from RoleBench. Role-play quality improved, but the models refused harmful AdvBench requests much less often, and villainous characters lost the most… - MPO: Multilingual Safety Alignment via Reward Gap Optimization (2025 · 7 citations)
Safety-tuned LLMs refuse harmful requests reliably in English but much less so in lower-resource languages. - TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent (2026 · 1 citation)
Most emotional support conversation (ESC) systems and benchmarks only measure empathetic wording in text-only settings.
Co-authors here
- Bing Qin ×4
- Jiahe Guo ×4
- Weixiang Zhao ×4
- Yanyan Zhao ×4
- An Zhang ×3
- Tat-Seng Chua ×3
- Ting Liu ×3
- Xingyu Sui ×3
- Yang Deng ×3
- Xinyang Han ×2
- Tongtong Wu
- Wenxuan Zhang
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026, ACL 2025 ×2
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
Cited by
Updated
This page in Markdown → https://md.research.elamur.ai/free/en/authors/yulin-hu/