Steven Feng

I'm a 2nd-year Stanford Computer Science PhD student and NSERC PGS-D scholar, working with the Stanford AI Lab and Stanford NLP Group. I am co-advised by Michael C. Frank and Noah Goodman and am part of the Language & Cognition (LangCog) and Computation & Cognition (CoCo) Labs. Previously, I was a master's student at Carnegie Mellon University (CMU) and an undergraduate student at the University of Waterloo.

My ultimate goal is to blend knowledge from multiple disciplines to advance AI research, specifically by teaching machines how to understand and generate human language and vision. I have explored ways to improve the controllability of language and visual generation models, incorporate and assess their reasoning capabilities, and integrate structured and multimodal information to enhance them. I am also exploring psychologically and cognitively-inspired methods to close the gap between human and LLM + VLM learning [1,2] while shedding further light on human cognitive models and our efficient language and vision acquisition capabilities.

I worked with Eduard Hovy at CMU's Language Technologies Institute and Malihe Alikhani at the University of Pittsburgh on research projects involving language generation, semantics, and data augmentation. Earlier, I worked at the University of Waterloo with Jesse Hoey.

My research contributions have been recognized with several publications at major conferences and a best paper award at INLG 2021. I am also an Honorable Mention for the Jessie W.H. Zou Memorial Award and CRA Outstanding Undergraduate Researcher Award.

I am a co-instructor for the Stanford CS25 Transformers course, and mentor and advise several students. I also led the organization of CtrlGen, a controllable generation workshop at NeurIPS 2021, and was involved in the GEM benchmark and workshop for NLG evaluation.

In my free time, I enjoy gaming, playing the piano and guitar, martial arts, and table tennis. I am also the founder and president of the Stanford Piano Society.

Email  /  CV  /  Google Scholar  /  Twitter  /  LinkedIn  /  GitHub  /  YouTube

profile photo

Recent News

  • June 2023: Starting my summer internship at Amazon! I'll be working as an Applied Scientist Intern on the Alexa AI team, focusing on improving the reasoning capabilities of LLMs.
  • Jan. 2023: Excited to be co-instructing Stanford's CS25 Transformers course! We feature amazing speakers each week.
  • Jan. 2023: Two papers accepted to EACL 2023! CHARD: clinical reasoning with text generation, and PANCETTA: automatically generating tongue twisters using language models!
  • Sept. 2022: Started my PhD in Computer Science at Stanford University! Very excited to work with the Stanford AI Lab and Stanford NLP Group.
  • Aug. 2022: Our PINEAPPLE paper on generating personifications was accepted to COLING 2022!
  • Feb. 2022: The recording of our CtrlGen NeurIPS workshop is publicly available here! It starts at around 35 minutes into the main recording.
  • Dec. 2021: Two papers accepted to AAAI 2022! One on visual grounding for commonsense in text generation and another on narrative reordering.
  • Sept. 2021: Thrilled that our SAPPHIRE paper on concept-to-text generation won BEST LONG PAPER at INLG 2021!
  • Aug. 2021: Varun and I gave a talk for Google Research! Recording here.
  • July 2021: Eduard Hovy and I were on The Data Exchange Podcast! Video here, audio and notes here.
  • May 2021: Our data augmentation survey paper was accepted to ACL 2021 Findings! It has received lots of attention on social media (e.g. this tweet, Sebastian Ruder's NLP Newsletter) and was one of the top 10 hottest machine learning papers in May 2021 (source: labml.ai).

Peer-Reviewed Publications and Conference Proceedings

CHARD: Clinical Health-Aware Reasoning Across Dimensions for Text Generation Models
Steven Y. Feng, Vivek Khetan, Bogdan Sacaleanu, Anatole Gershman, Eduard Hovy
Accepted to European Chapter of the Association for Computational Linguistics (EACL) 2023
Abstract / Bibtex

PANCETTA: Phoneme Aware Neural Completion to Elicit Tongue Twisters Automatically
Sedrick Scott Keh, Steven Y. Feng*, Varun Gangal*, Malihe Alikhani, Eduard Hovy
Accepted to European Chapter of the Association for Computational Linguistics (EACL) 2023
Abstract / Bibtex / GitHub

PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personification data for Learning Enhanced generation
Sedrick Scott Keh, Kevin Lu, Varun Gangal*, Steven Y. Feng*, Harsh Jhamtani, Malihe Alikhani, Eduard Hovy
Proceedings of International Conference on Computational Linguistics (COLING) 2022
Abstract at TADA 2021: Conference on New Directions in Analyzing Text as Data
Abstract / Bibtex / GitHub / Talk / Presentation Slides / Poster

Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models
Steven Y. Feng, Kevin Lu, Zhuofu Tao, Malihe Alikhani, Teruko Mitamura, Eduard Hovy, Varun Gangal
Proceedings of AAAI Conference on Artificial Intelligence 2022 (Acceptance rate: 15%)
Accepted to AKBC 2021 Commonsense Reasoning and Knowledge Bases (CSKB) Workshop.
Abstract / Bibtex / GitHub / Presentation Slides / Poster

NAREOR: The Narrative Reordering Problem
Varun Gangal*, Steven Y. Feng*, Malihe Alikhani, Teruko Mitamura, Eduard Hovy
Proceedings of AAAI Conference on Artificial Intelligence 2022 (Acceptance rate: 15%)
Abstract / Bibtex / GitHub / Presentation Slides / Poster

SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
Steven Y. Feng, Jessica Huynh, Chaitanya Narisetty, Eduard Hovy, Varun Gangal
Proceedings of International Conference on Natural Language Generation (INLG) 2021 [Best Long Paper]
Abstract / Bibtex / GitHub / Poster

A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng*, Varun Gangal*, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard Hovy
Proceedings of Association for Computational Linguistics (ACL) 2021 Findings [Long Paper]
Abstract / Bibtex / GitHub / Podcast (with Ed Hovy) / Talk (for Google Research) / Presentation Slides / Poster

GenAug: Data Augmentation for Finetuning Text Generators
Steven Y. Feng*, Varun Gangal*, Dongyeop Kang, Teruko Mitamura, Eduard Hovy
Proceedings of EMNLP 2020 Deep Learning Inside Out (DeeLIO) Workshop [Long Paper]
Abstract / Bibtex / GitHub / Presentation Slides

ALOHA: Artificial Learning of Human Attributes for Dialogue Agents
Aaron W. Li, Veronica Jiang*, Steven Y. Feng*, Julia Sprague, Wei Zhou, Jesse Hoey
Proceedings of AAAI Conference on Artificial Intelligence 2020 (Acceptance rate: 20.6%) [Oral]
Abstract / Bibtex / GitHub

Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange
Steven Y. Feng*, Aaron W. Li*, Jesse Hoey
Proceedings of Empirical Methods in Natural Language Processing (EMNLP) 2019 (Acceptance rate: 23.8%) [Long Paper]
Abstract / Bibtex / GitHub / Poster / News Article

* Equal Contribution

Talks and Interviews

July 2021: Eduard Hovy and I were on The Data Exchange Podcast with Ben Lorica. We discuss data augmentation for NLP (inspired by our survey paper) and challenges + future directions in NLP and machine learning research. Audio and notes here.



Aug. 2021: Varun and I gave a talk (to over 100 attendees) for Google Research about data augmentation for NLP (inspired by our survey paper). We also touch upon NL-Augmenter and our CtrlGen Workshop at NeurIPS 2021.



Teaching and Instruction

Stanford's CS25: Transformers United - I am a co-instructor for Stanford's CS25 course! We feature in-depth discussion from exciting speakers each week about cutting-edge research in Transformers for various ML areas/applications. Some speakers so far include Andrej Karpathy, Jan Leike (OpenAI), and Jason Wei (OpenAI, prev. Google Brain). Some class photos with them below!

Karpathy1
Jan

Mentorship and Advising

  • Sedrick Scott Keh [CMU Master's of Machine Learning (MSML), Class of 2022]
  • Mentoring several research projects on controllable and creative text generation [e.g. paper1, paper2].
  • Kevin Lu [University of Waterloo Undergrad, Computer Science, Class of 2026]
  • Mentored several research projects on controllable, creative, and visually-grounded text generation [e.g. paper1, paper2].
  • Zhuofu (Derek) Tao [UCLA Ph.D. in Electrical Engineering, Class of 2025]
  • Mentored a research project on controllable and visually-grounded text generation [paper].
  • Jerry Huang, Hongru Xiang, Xintao (Cynthia) Zhu, Saidi Tang [University of Waterloo Undergrads, Software Engineering, Class of 2022]
  • Advised their software engineering capstone project on text simplification for ESL students.

Last Updated: Sept. 15, 2023 Site Template