| 2026 | AAAI | Learning from Reasoning Failures via Synthetic Data Generation. | Gabriela Ben Melech Stan, Estelle Aflalo, Avinash Madasu, Vasudev Lal, Phillip Howard |
| 2025 | CVPR | Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders. | Matthew Lyle Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng |
| 2025 | EMNLP | Pruning the Paradox: How CLIP's Most Informative Heads Enhance Performance While Amplifying Bias. | Avinash Madasu, Vasudev Lal, Phillip Howard |
| 2025 | EMNLP | Transformer-Based Temporal Information Extraction and Application: A Review. | Xin Su, Phillip Howard, Steven Bethard |
| 2025 | ICCV | Probing the Representational Power of Sparse Autoencoders in Vision Models. | Matthew L. Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng |
| 2025 | ICCV | Debias Your Large Multi-Modal Model at Test-Time via Non-Contrastive Visual Attribute Steering. | Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard |
| 2025 | ICML | SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs. | Xin Su, Man Luo, Kris W. Pan, Tien Pei Chou, Vasudev Lal, Phillip Howard |
| 2025 | NAACL | Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals. | Phillip Howard, Kathleen C. Fraser, Anahita Bhiwandiwalla, Svetlana Kiritchenko |
| 2025 | NAACL | LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model Compression. | Souvik Kundu, Anahita Bhiwandiwalla, Sungduk Yu, Phillip Howard, Tiep Le, Sharath Nittur Sridhar, David Cobbley, Hao Kang, Vasudev Lal |
| 2024 | CVPR | SocialCounterfactuals: Probing and Mitigating Intersectional Social Biases in Vision-Language Models with Counterfactual Examples. | Phillip Howard, Avinash Madasu, Tiep Le, Gustavo A. Lujan-Moreno, Anahita Bhiwandiwalla, Vasudev Lal |
| 2024 | EACL | NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation. | Shachar Rosenman, Vasudev Lal, Phillip Howard |
| 2024 | NAACL | NeuroComparatives: Neuro-Symbolic Distillation of Comparative Knowledge. | Phillip Howard, Junlin Wang, Vasudev Lal, Gadi Singer, Yejin Choi, Swabha Swayamdipta |
| 2024 | NAACL | Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning. | Xin Su, Tiep Le, Steven Bethard, Phillip Howard |
| 2023 | EMNLP | Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering. | Xin Su, Phillip Howard, Nagib Hakim, Steven Bethard |
| 2022 | CIKM | Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs. | Phillip Howard, Arden Ma, Vasudev Lal, Ana Paula Simes, Daniel Korat, Oren Pereg, Moshe Wasserblat, Gadi Singer |
| 2022 | EMNLP | NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation. | Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi, Swabha Swayamdipta |
| 2021 | EACL | InterpreT: An Interactive Visualization Tool for Interpreting Transformers. | Vasudev Lal, Arden Ma, Estelle Aflalo, Phillip Howard, Ana Paula Simes, Daniel Korat, Oren Pereg, Gadi Singer, Moshe Wasserblat |