Tyler LaBonte

13 papers A* 2A 2Journal 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Phi-4-reasoning-vision-15B Technical Report.
CoRR
Jyoti Aneja, Michael Harrison, Neel Joshi, Tyler LaBonte, John Langford, Eduardo Salinas
2025 J jnl
On the Unreasonable Effectiveness of Last-layer Retraining.
CoRR
John C. Hill, Tyler LaBonte, Xinchen Zhang, Vidya Muthukumar
2025 A conf
Task Shift: From Classification to Regression in Overparameterized Linear Models.
AISTATS
Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar
2025 J jnl
Task Shift: From Classification to Regression in Overparameterized Linear Models.
CoRR
Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar
2024 A* conf
The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations.
NeurIPS
Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar
2024 J jnl
The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations.
CoRR
Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar
2023 A conf
Scaling Novel Object Detection with Weakly Supervised Detection Transformers.
WACV
Tyler LaBonte, Yale Song, Xin Wang, Vibhav Vineet, Neel Joshi
2023 A* conf
Towards Last-layer Retraining for Group Robustness with Fewer Annotations.
NeurIPS
Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar
2023 J jnl
Towards Last-layer Retraining for Group Robustness with Fewer Annotations.
CoRR
Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar
2022 J jnl
Scaling Novel Object Detection with Weakly Supervised Detection Transformers.
CoRR
Tyler LaBonte, Yale Song, Xin Wang, Vibhav Vineet, Neel Joshi
2022 J jnl
Student misconceptions of dynamic programming: a replication study.
Comput. Sci. Educ.
Michael Shindler, Natalia Pinpin, Mia Markovic, Frederick Reiber, Jee Hoon Kim, Giles Pierre Nunez Carlos, Mine Dogucu, Mark Hong, Michael Luu, Brian Anderson, Aaron Cote, Matthew Ferland, Palak Jain, Tyler LaBonte, Leena Mathur, Ryan Moreno, Ryan Sakuma
2020 J jnl
Quantifying the Unknown: Impact of Segmentation Uncertainty on Image-Based Simulations.
CoRR
Michael C. Krygier, Tyler LaBonte, Carianne Martinez, Chance Norris, Krish Sharma, Lincoln N. Collins, Partha P. Mukherjee, Scott A. Roberts
2019 J jnl
We Know Where We Don't Know: 3D Bayesian CNNs for Uncertainty Quantification of Binary Segmentations for Material Simulations.
CoRR
Tyler LaBonte, Carianne Martinez, Scott A. Roberts