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2020 – today
- 2024
[c11]Shraddha Barke, Christian Pölitz, Carina Negreanu, Benjamin 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. NAACL-HLT (Findings) 2024: 626-638- [i4]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 abs/2402.11734 (2024) - 2023
- [c10]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: 598:1-598:31 - [i3]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 abs/2304.06597 (2023)
2010 – 2019
- 2019
- [c9]Judith Borghouts, Andrew D. Gordon, Advait Sarkar, Neil Toronto:
End-User Probabilistic Programming. QEST 2019: 3-24 - [i2]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 abs/1905.13072 (2019) - 2018
- [c8]Advait Sarkar, Andrew D. Gordon, Simon Peyton Jones, Neil Toronto:
Calculation View: multiple-representation editing in spreadsheets. VL/HCC 2018: 85-93 - 2015
- [c7]Neil Toronto, Jay McCarthy, David Van Horn:
Running Probabilistic Programs Backwards. ESOP 2015: 53-79 - 2014
- [j1]Neil Toronto, Jay McCarthy:
Practically Accurate Floating-Point Math. Comput. Sci. Eng. 16(4): 80-95 (2014) - [i1]Neil Toronto, Jay McCarthy, David Van Horn:
Running Probabilistic Programs Backwards. CoRR abs/1412.4053 (2014) - 2013
- [c6]Vincent St-Amour, Neil Toronto:
Experience report: applying random testing to a base type environment. ICFP 2013: 351-356 - 2012
- [c5]Neil Toronto, Jay McCarthy:
Computing in Cantor's Paradise with λ ZFC. FLOPS 2012: 290-306 - 2010
- [c4]Neil Toronto, Jay McCarthy:
From Bayesian Notation to Pure Racket via Discrete Measure-Theoretic Probability in λ ZFC. IFL 2010: 89-104
2000 – 2009
- 2009
- [c3]Neil Toronto, Bryan S. Morse, Kevin D. Seppi, Dan Ventura:
Super-resolution via recapture and Bayesian effect modeling. CVPR 2009: 2388-2395 - 2007
- [c2]Neil Toronto, Bryan S. Morse, Dan Ventura, Kevin D. Seppi:
The Hough Transform's Implicit Bayesian Foundation. ICIP (4) 2007: 377-380 - 2006
- [c1]Neil Toronto, Dan Ventura:
Learning Quantum Operators From Quantum State Pairs. IEEE Congress on Evolutionary Computation 2006: 2607-2612
Coauthor Index
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