Ingenium: Engaging Novice Students with Latin Grammar. - Sharon Zhou; Ivy J. Livingston; Mark Schiefsky; Stuart M. Shieber; Krzysztof Z. Gajos (CHI, 2016)

Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms. - Snehalkumar (Neil) S. Gaikwad; Durim Morina; Adam Ginzberg; Catherine A. Mullings; Shirish Goyal; Dilrukshi Gamage; Christopher Diemert; Mathias Burton; Sharon Zhou; Mark E. Whiting; Karolina R. Ziulkoski; Alipta Ballav; et al. (UIST, 2016)

The Daemo Crowdsourcing Marketplace. - Snehalkumar (Neil) S. Gaikwad; Mark E. Whiting; Dilrukshi Gamage; Catherine A. Mullings; Dinesh Majeti; Shirish Goyal; Aaron Gilbee; Nalin Chhibber; Adam Ginzberg; Angela Richmond-Fuller; Sekandar Matin; Vibhor Sehgal; et al. (CSCW Companion, 2017)

Prototype Tasks: Improving Crowdsourcing Results through Rapid, Iterative Task Design. - Snehalkumar (Neil) S. Gaikwad; Nalin Chhibber; Vibhor Sehgal; Alipta Ballav; Catherine A. Mullings; Ahmed Nasser; Angela Richmond-Fuller; Aaron Gilbee; Dilrukshi Gamage; Mark E. Whiting; Sharon Zhou; Sekandar Matin; et al. (CoRR, 2017)

In Search of the Dream Team: Temporally Constrained Multi-Armed Bandits for Identifying Effective Team Structures. - Sharon Zhou; Melissa A. Valentine; Michael S. Bernstein (CHI, 2018)

Shared Autonomy for an Interactive AI System. - Sharon Zhou; Tong Mu; Karan Goel; Michael S. Bernstein; Emma Brunskill (UIST (Adjunct Volume), 2018)

HYPE: Human-eYe Perceptual Evaluation of Generative Models. - Sharon Zhou; Mitchell L. Gordon; Ranjay Krishna; Austin Narcomey; Durim Morina; Michael S. Bernstein (DGS@ICLR, 2019)

HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models. - Sharon Zhou; Mitchell L. Gordon; Ranjay Krishna; Austin Narcomey; Li Fei-Fei 001; Michael S. Bernstein (NeurIPS, 2019)

Countdown Regression: Sharp and Calibrated Survival Predictions. - Anand Avati; Tony Duan; Sharon Zhou; Kenneth Jung; Nigam H. Shah; Andrew Y. Ng (UAI, 2019)

Approximating Human Judgment of Generated Image Quality. - Y. Alex Kolchinski; Sharon Zhou; Shengjia Zhao; Mitchell L. Gordon; Stefano Ermon (CoRR, 2019)

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. - Nick A. Phillips; Pranav Rajpurkar; Mark Sabini; Rayan Krishnan; Sharon Zhou; Anuj Pareek; Nguyet Minh Phu; Chris Wang; Mudit Jain; Du Nguyen Duong; Steven Q. H. Truong; Andrew Y. Ng; et al. (ML4H@NeurIPS, 2020)

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. - Sharon Zhou; Eric Zelikman; Fred Lu; Andrew Y. Ng; Stefano Ermon (CoRR, 2020)

CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. - Nick A. Phillips; Pranav Rajpurkar; Mark Sabini; Rayan Krishnan; Sharon Zhou; Anuj Pareek; Nguyet Minh Phu; Chris Wang; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models. - Eric Zelikman; Sharon Zhou; Jeremy Irvin; Cooper Raterink; Hao Sheng 003; Jack Kelly; Ram Rajagopal; Andrew Y. Ng; David John Gagne II (CoRR, 2020)

ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery. - Jeremy Irvin; Hao Sheng 003; Neel Ramachandran; Sonja Johnson-Yu; Sharon Zhou; Kyle Story; Rose Rustowicz; Cooper Elsworth; Kemen Austin; Andrew Y. Ng (CoRR, 2020)

Establishing an evaluation metric to quantify climate change image realism. - Sharon Zhou; Alexandra Luccioni; Gautier Cosne; Michael S. Bernstein; Yoshua Bengio (Mach. Learn. Sci. Technol., 2020)

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. - Sharon Zhou; Eric Zelikman; Fred Lu; Andrew Y. Ng; Gunnar E. Carlsson; Stefano Ermon (ICLR, 2021)

Data augmentation with Mobius transformations. - Sharon Zhou; Jiequan Zhang; Hang Jiang; Torbjörn Lundh; Andrew Y. Ng (Mach. Learn. Sci. Technol., 2021)

On the evaluation of deep generative models. - Sharon Zhou (2021)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Banishing LLM Hallucinations Requires Rethinking Generalization. - Johnny Li; Saksham Consul; Eda Zhou; James Wong; Naila Farooqui; Yuxin Ye; Nithyashree Manohar; Zhuxiaona Wei; Tian Wu; Ben Echols; Sharon Zhou; Gregory F. Diamos (CoRR, 2024)