Neil Toronto

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 6

Top Topics

Language Modelling

Top Venues

Comput. Sci. Eng.

Publications

Shraddha Barke, Christian Pölitz, Carina Suzana Negreanu, Benjamin G. Zorn, José Cambronero, Andrew D. Gordon, Vu Le, Elnaz Nouri, Nadia Polikarpova, Advait Sarkar, Brian Slininger, Neil Toronto, Jack Williams
Solving Data-centric Tasks using Large Language Models. CoRR (2024)
Michael Xieyang Liu, Advait Sarkar, Carina Negreanu, Benjamin G. Zorn, Jack Williams, Neil Toronto, Andrew D. Gordon
"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models. CHI (2023)
Michael Xieyang Liu, Advait Sarkar, Carina Negreanu, Ben Zorn, Jack Williams, Neil Toronto, Andrew D. Gordon
"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models. CoRR (2023)
Judith Borghouts, Andrew D. Gordon, Advait Sarkar, Kenton P. O'Hara, Neil Toronto
Somewhere Around That Number: An Interview Study of How Spreadsheet Users Manage Uncertainty. CoRR (2019)
Judith Borghouts, Andrew D. Gordon, Advait Sarkar, Neil Toronto
End-User Probabilistic Programming. QEST (2019)
Advait Sarkar, Andrew D. Gordon, Simon Peyton Jones, Neil Toronto
Calculation View: multiple-representation editing in spreadsheets. VL/HCC (2018)
Neil Toronto, Jay McCarthy, David Van Horn
Running Probabilistic Programs Backwards. ESOP (2015)
Neil Toronto, Jay McCarthy, David Van Horn
Running Probabilistic Programs Backwards. CoRR (2014)
Neil Toronto, Jay McCarthy
Practically Accurate Floating-Point Math. Comput. Sci. Eng. 16 (4) (2014)
Vincent St-Amour, Neil Toronto
Experience report: applying random testing to a base type environment. ICFP (2013)
Neil Toronto, Jay McCarthy
Computing in Cantor's Paradise with λ ZFC. FLOPS (2012)
Neil Toronto, Jay McCarthy
From Bayesian Notation to Pure Racket via Discrete Measure-Theoretic Probability in λ ZFC. IFL (2010)
Neil Toronto, Bryan S. Morse, Kevin D. Seppi, Dan Ventura
Super-resolution via recapture and Bayesian effect modeling. CVPR (2009)
Neil Toronto, Bryan S. Morse, Dan Ventura, Kevin D. Seppi
The Hough Transform's Implicit Bayesian Foundation. ICIP (4) (2007)
Neil Toronto, Dan Ventura
Learning Quantum Operators From Quantum State Pairs. IEEE Congress on Evolutionary Computation (2006)