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ORCIDPhillip Howard
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- affiliation: Arizona State University, Tempe, USA
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2020 – today
- 2024
[c8]Shachar Rosenman, Vasudev Lal, Phillip Howard:
NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation. EACL (Demonstrations) 2024: 159-167- 2023
- [c7]Xin Su, Phillip Howard, Nagib Hakim, Steven Bethard:
Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering. EMNLP (Findings) 2023: 948-966 - [c6]Tiep Le, Vasudev Lal, Phillip Howard:
COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs. NeurIPS 2023 - [i11]Gadi Singer, Joscha Bach, Tetiana Grinberg, Nagib Hakim, Phillip Howard, Vasudev Lal, Zev Rivlin:
Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding. CoRR abs/2303.12084 (2023) - [i10]Phillip Howard, Junlin Wang, Vasudev Lal, Gadi Singer, Yejin Choi, Swabha Swayamdipta:
NeuroComparatives: Neuro-Symbolic Distillation of Comparative Knowledge. CoRR abs/2305.04978 (2023) - [i9]Tiep Le, Vasudev Lal, Phillip Howard:
COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs. CoRR abs/2309.14356 (2023) - [i8]Phillip Howard, Avinash Madasu, Tiep Le, Gustavo A. Lujan-Moreno, Vasudev Lal:
Probing Intersectional Biases in Vision-Language Models with Counterfactual Examples. CoRR abs/2310.02988 (2023) - [i7]Xin Su, Phillip Howard, Nagib Hakim, Steven Bethard:
Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering. CoRR abs/2310.19292 (2023) - [i6]Xin Su, Tiep Le, Steven Bethard, Phillip Howard:
Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning. CoRR abs/2311.08505 (2023) - [i5]Shachar Rosenman, Vasudev Lal, Phillip Howard:
NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation. CoRR abs/2311.12229 (2023) - [i4]Phillip Howard, Avinash Madasu, Tiep Le, Gustavo A. Lujan-Moreno, Anahita Bhiwandiwalla, Vasudev Lal:
Probing and Mitigating Intersectional Social Biases in Vision-Language Models with Counterfactual Examples. CoRR abs/2312.00825 (2023) - 2022
- [c5]Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip Ryan Howard, Tetiana Grinberg, Nagib Hakim, George Karypis:
TempoQR: Temporal Question Reasoning over Knowledge Graphs. AAAI 2022: 5825-5833 - [c4]Gadi Singer, Joscha Bach, Tetiana Grinberg
, Nagib Hakim, Phillip Ryan Howard, Vasudev Lal, Zev Rivlin:
Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding. AGI 2022: 404-412 - [c3]Phillip Howard, Arden Ma, Vasudev Lal, Ana Paula Simões, Daniel Korat, Oren Pereg, Moshe Wasserblat, Gadi Singer:
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs. CIKM 2022: 780-790 - [c2]Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi, Swabha Swayamdipta:
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation. EMNLP (Findings) 2022: 5056-5072 - [i3]Phillip Howard, Arden Ma, Vasudev Lal, Ana Paula Simões, Daniel Korat, Oren Pereg, Moshe Wasserblat, Gadi Singer:
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs. CoRR abs/2210.10144 (2022) - [i2]Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi, Swabha Swayamdipta:
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation. CoRR abs/2210.12365 (2022) - 2021
- [c1]Vasudev Lal, Arden Ma, Estelle Aflalo, Phillip Howard, Ana Paula Simões, Daniel Korat, Oren Pereg, Gadi Singer, Moshe Wasserblat:
InterpreT: An Interactive Visualization Tool for Interpreting Transformers. EACL (System Demonstrations) 2021: 135-142 - [i1]Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Soji Adeshina, Phillip Ryan Howard, Tetiana Grinberg, Nagib Hakim, George Karypis:
TempoQR: Temporal Question Reasoning over Knowledge Graphs. CoRR abs/2112.05785 (2021)
2010 – 2019
- 2018
- [j2]Gustavo A. Lujan-Moreno, Phillip Ryan Howard, Omar Rojas, Douglas C. Montgomery:
Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-study. Expert Syst. Appl. 109: 195-205 (2018) - [j1]Phillip Howard, Daniel W. Apley, George Runger:
Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis. IEEE Trans. Neural Networks Learn. Syst. 29(1): 156-166 (2018) - 2016
- [b1]Phillip Ryan Howard:
Distinct Feature Learning and Nonlinear Variation Pattern Discovery Using Regularized Autoencoders. Arizona State University, Tempe, USA, 2016
Coauthor Index
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last updated on 2024-04-25 02:32 CEST by the dblp team
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