| Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-study GA Lujan-Moreno, PR Howard, OG Rojas, DC Montgomery Expert Systems with Applications 109, 195-205, 2018 | 176 | 2018 |
| Tempoqr: temporal question reasoning over knowledge graphs C Mavromatis, PL Subramanyam, VN Ioannidis, A Adeshina, PR Howard, ... Proceedings of the AAAI conference on artificial intelligence 36 (5), 5825-5833, 2022 | 65 | 2022 |
| Coco-counterfactuals: Automatically constructed counterfactual examples for image-text pairs T Le, V Lal, P Howard Advances in Neural Information Processing Systems 36, 2024 | 24 | 2024 |
| Neurocounterfactuals: Beyond minimal-edit counterfactuals for richer data augmentation P Howard, G Singer, V Lal, Y Choi, S Swayamdipta arXiv preprint arXiv:2210.12365, 2022 | 23 | 2022 |
| InterpreT: An interactive visualization tool for interpreting transformers V Lal, A Ma, E Aflalo, P Howard, A Simoes, D Korat, O Pereg, G Singer, ... Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 20 | 2021 |
| Cross-domain aspect extraction using transformers augmented with knowledge graphs P Howard, A Ma, V Lal, AP Simoes, D Korat, O Pereg, M Wasserblat, ... Proceedings of the 31st acm international conference on information …, 2022 | 13 | 2022 |
| Automated data mining methods for identifying energy efficiency opportunities using whole-building electricity data P Howard, PE T Agami Reddy PhD, PE Srinivas Katipamula PhD ASHRAE Transactions 122, 422, 2016 | 12 | 2016 |
| Identifying nonlinear variation patterns with deep autoencoders P Howard, DW Apley, G Runger IISE Transactions 50 (12), 1089-1103, 2018 | 11 | 2018 |
| Distinct variation pattern discovery using alternating nonlinear principal component analysis P Howard, DW Apley, G Runger IEEE transactions on neural networks and learning systems 29 (1), 156-166, 2016 | 11 | 2016 |
| SocialCounterfactuals: Probing and Mitigating Intersectional Social Biases in Vision-Language Models with Counterfactual Examples P Howard, A Madasu, T Le, GL Moreno, A Bhiwandiwalla, V Lal Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 10 | 2024 |
| Neuroprompts: An adaptive framework to optimize prompts for text-to-image generation S Rosenman, V Lal, P Howard arXiv preprint arXiv:2311.12229, 2023 | 8 | 2023 |
| Probing and mitigating intersectional social biases in vision-language models with counterfactual examples P Howard, A Madasu, T Le, GA Lujan-Moreno, A Bhiwandiwalla, V Lal CoRR, 2023 | 7 | 2023 |
| Uncovering Bias in Large Vision-Language Models with Counterfactuals P Howard, A Bhiwandiwalla, KC Fraser, S Kiritchenko arXiv preprint arXiv:2404.00166, 2024 | 6 | 2024 |
| Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals P Howard, KC Fraser, A Bhiwandiwalla, S Kiritchenko arXiv preprint arXiv:2405.20152, 2024 | 5 | 2024 |
| Neurocomparatives: Neuro-symbolic distillation of comparative knowledge P Howard, J Wang, V Lal, G Singer, Y Choi, S Swayamdipta arXiv preprint arXiv:2305.04978, 2023 | 5 | 2023 |
| Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning X Su, T Le, S Bethard, P Howard arXiv preprint arXiv:2311.08505, 2023 | 3 | 2023 |
| Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering X Su, P Howard, N Hakim, S Bethard arXiv preprint arXiv:2310.19292, 2023 | 3 | 2023 |
| Is your paper being reviewed by an llm? investigating ai text detectability in peer review S Yu, M Luo, A Madasu, V Lal, P Howard arXiv preprint arXiv:2410.03019, 2024 | 2 | 2024 |
| Probing intersectional biases in vision-language models with counterfactual examples P Howard, A Madasu, T Le, GL Moreno, V Lal arXiv preprint arXiv:2310.02988, 2023 | 2 | 2023 |
| Training-Free Mitigation of Language Reasoning Degradation After Multimodal Instruction Tuning N Ratzlaff, M Luo, X Su, V Lal, P Howard arXiv preprint arXiv:2412.03467, 2024 | 1 | 2024 |
