| Visual commonsense in pretrained unimodal and multimodal models C Zhang, B Van Durme, Z Li, E Stengel-Eskin Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 42 | 2022 |
| A Discriminative Neural Model for Cross-Lingual Word Alignment E Stengel-Eskin, TR Su, M Post, B Van Durme Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 36 | 2019 |
| Super-clevr: A virtual benchmark to diagnose domain robustness in visual reasoning Z Li, X Wang, E Stengel-Eskin, A Kortylewski, W Ma, B Van Durme, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 32 | 2023 |
| The universal decompositional semantics dataset and decomp toolkit AS White, E Stengel-Eskin, S Vashishtha, V Govindarajan, DA Reisinger, ... Proceedings of the Twelfth Language Resources and Evaluation Conference, 2019 | 31 | 2019 |
| Guiding multi-step rearrangement tasks with natural language instructions E Stengel-Eskin, A Hundt, Z He, A Murali, N Gopalan, M Gombolay, ... Conference on Robot Learning, 1486-1501, 2022 | 25 | 2022 |
| Universal Decompositional Semantic Parsing E Stengel-Eskin, AS White, S Zhang, B Van Durme Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 22* | 2020 |
| Gtbench: Uncovering the strategic reasoning limitations of llms via game-theoretic evaluations J Duan, R Zhang, J Diffenderfer, B Kailkhura, L Sun, E Stengel-Eskin, ... NeurIPS 2024, 2024 | 20 | 2024 |
| Polyglot and Speech Corpus Tools: A System for Representing, Integrating, and Querying Speech Corpora. M McAuliffe, E Stengel-Eskin, M Socolof, M Sonderegger INTERSPEECH, 3887-3891, 2017 | 18 | 2017 |
| Calibrating concepts and operations: Towards symbolic reasoning on real images Z Li, E Stengel-Eskin, Y Zhang, C Xie, QH Tran, B Van Durme, A Yuille Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 17 | 2021 |
| Calibrated interpretation: Confidence estimation in semantic parsing E Stengel-Eskin, B Van Durme Transactions of the Association for Computational Linguistics 11, 1213-1231, 2023 | 12 | 2023 |
| Joint Universal Syntactic and Semantic Parsing E Stengel-Eskin, K Murray, S Zhang, AS White, B Van Durme Transactions of the Association for Computational Linguistics 9, 756-773, 2021 | 10 | 2021 |
| Contrastive region guidance: Improving grounding in vision-language models without training D Wan, J Cho, E Stengel-Eskin, M Bansal arXiv preprint arXiv:2403.02325, 2024 | 9 | 2024 |
| Why did the chicken cross the road? Rephrasing and analyzing ambiguous questions in VQA E Stengel-Eskin, J Guallar-Blasco, Y Zhou, B Van Durme Proceedings of the 61st Annual Meeting of the Association for Computational …, 2022 | 8 | 2022 |
| Rephrase, augment, reason: Visual grounding of questions for vision-language models A Prasad, E Stengel-Eskin, M Bansal The Twelfth International Conference on Learning Representations, 2023 | 7 | 2023 |
| Zero and few-shot semantic parsing with ambiguous inputs E Stengel-Eskin, K Rawlins, B Van Durme The Twelfth International Conference on Learning Representations, 2023 | 7 | 2023 |
| VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos Z Wang*, S Yu*, E Stengel-Eskin*, J Yoon, F Cheng, G Bertasius, ... arXiv preprint arXiv:2405.19209, 2024 | 6 | 2024 |
| Regal: Refactoring programs to discover generalizable abstractions E Stengel-Eskin, A Prasad, M Bansal Forty-first International Conference on Machine Learning, 2024 | 6 | 2024 |
| Iterative paraphrastic augmentation with discriminative span alignment R Culkin, JE Hu, E Stengel-Eskin, G Qin, BV Durme Transactions of the Association for Computational Linguistics 9, 494-509, 2021 | 6 | 2021 |
| Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in LLMs? P Hase, T Hofweber, X Zhou, E Stengel-Eskin, M Bansal arXiv preprint arXiv:2406.19354, 2024 | 4 | 2024 |
| Did you mean...? Confidence-based trade-offs in semantic parsing E Stengel-Eskin, B Van Durme Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 3 | 2023 |
