--- title: "Tenghao Huang — author profile and papers in our library" description: "Tenghao Huang, University of Southern California: 2 papers on Elamur Research (2022–2024), h-index 3 — affiliations, topics, co-authors…" canonical: "https://research.elamur.ai/free/en/authors/tenghao-huang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/tenghao-huang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Tenghao Huang # Tenghao Huang Tenghao Huang has 2 papers in our library, in 2022–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Colin Raffel](https://md.research.elamur.ai/free/en/authors/colin-raffel/), [Derek Tam](https://md.research.elamur.ai/free/en/authors/derek-tam/), [Haokun Liu](https://md.research.elamur.ai/free/en/authors/haokun-liu/). 2 papers in our library · 2022–2024 [OpenAlex](https://openalex.org/A5029827648) · [ORCID](https://orcid.org/0009-0007-5498-477X) · [**h-index 3**](https://openalex.org/authors/A5029827648) · [13 works](https://openalex.org/works?filter=author.id:A5029827648) · [58 citations](https://openalex.org/works?filter=author.id:A5029827648&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/tenghao-huang/#papers) · [🔗 Cited 415 times in our library](https://md.research.elamur.ai/free/en/authors/tenghao-huang/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #3087](https://md.research.elamur.ai/free/en/paper-stars/page/31/#star-3087) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Tenghao+Huang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Tenghao+Huang) · [dblp](https://dblp.org/search?q=Tenghao+Huang) · [ACL Anthology](https://aclanthology.org/search/?q=Tenghao+Huang) ## Affiliations [🎓**University of Southern California** Los Angeles · United States 2023–2025 · 10 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-southern-california/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) 💡 Concepts 2 Key ideas and methods explained on our concept pages.[Few-shot learning · 1 work](https://md.research.elamur.ai/free/en/concepts/few-shot-learning/) · [Fine-tuning · 1 work](https://md.research.elamur.ai/free/en/concepts/fine-tuning/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/tenghao-huang/year/2024/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/tenghao-huang/year/2022/) ## Papers The most cited first (OpenAlex and our library). 1. **[Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://md.research.elamur.ai/free/en/papers/liu-2022-few-shot-parameter-efficient-fine/)** *(2022 · 754 citations)* Few-shot in-context learning (ICL) lets a large language model take on a new task without training. However, every prediction must reprocess all demonstration examples, which is costly, and results shift with prompt wording and example order. The authors test whether parameter-efficient fine-tuning (PEFT) is a better… 2. **[Are Large Language Models Capable of Generating Human-Level Narratives?](https://md.research.elamur.ai/free/en/papers/tian-2024-are-large-language-models-capable/)** *(2024 · 67 citations)* The paper asks whether LLM-written stories match human ones in structure, not just fluency. The authors propose a framework that examines narrative discourse at three levels: macro story arcs (seven Vonnegut-style types), meso turning points (five types following Papalampidi et al., 2019) and micro affect (arousal… ## All works 3 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. **[Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://md.research.elamur.ai/free/en/papers/liu-2022-few-shot-parameter-efficient-fine/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.*2022 · 754 citations* 2. **[Are Large Language Models Capable of Generating Human-Level Narratives?](https://md.research.elamur.ai/free/en/papers/tian-2024-are-large-language-models-capable/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yufei Tian, Tenghao Huang, Miri Liu, et al.*2024 · 67 citations* 3. **[WebDS: An End-to-End Benchmark for Web-based Data Science ↗](https://arxiv.org/abs/2508.01222) arXiv (Cornell University) · no summary yet**Hsu, Ethan et al.*2025 · 1 citation* ## Co-authors here 9 co-authors with a page, the most papers together first. - [Colin Raffel](https://md.research.elamur.ai/free/en/authors/colin-raffel/) - [Derek Tam](https://md.research.elamur.ai/free/en/authors/derek-tam/) - [Haokun Liu](https://md.research.elamur.ai/free/en/authors/haokun-liu/) - [Jonathan May](https://md.research.elamur.ai/free/en/authors/jonathan-may/) - [Miri Liu](https://md.research.elamur.ai/free/en/authors/miri-liu/) - [Mohit Bansal](https://md.research.elamur.ai/free/en/authors/mohit-bansal/) - [Muhao Chen](https://md.research.elamur.ai/free/en/authors/muhao-chen/) - [Nanyun Peng](https://md.research.elamur.ai/free/en/authors/nanyun-peng/) - [Yufei Tian](https://md.research.elamur.ai/free/en/authors/yufei-tian/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2024](https://md.research.elamur.ai/free/en/venues/emnlp/2024/) - [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2022](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2022/) ## Cited by Papers of our library cite their works 415 times (of the 149,439 papers whose bibliographies we read); [82 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/tenghao-huang/cited-by/). Updated 31 October 2026