Newsqa: A machine comprehension dataset A Trischler, T Wang, X Yuan, J Harris, A Sordoni, P Bachman, K Suleman arXiv preprint arXiv:1611.09830, 2016 | 968 | 2016 |
Frames: a corpus for adding memory to goal-oriented dialogue systems LE Asri, H Schulz, S Sharma, J Zumer, J Harris, E Fine, R Mehrotra, ... arXiv preprint arXiv:1704.00057, 2017 | 309 | 2017 |
A sequence-to-sequence model for user simulation in spoken dialogue systems LE Asri, J He, K Suleman arXiv preprint arXiv:1607.00070, 2016 | 151 | 2016 |
Policy networks with two-stage training for dialogue systems M Fatemi, LE Asri, H Schulz, J He, K Suleman arXiv preprint arXiv:1606.03152, 2016 | 112 | 2016 |
Natural language comprehension with the epireader A Trischler, Z Ye, X Yuan, K Suleman arXiv preprint arXiv:1606.02270, 2016 | 107 | 2016 |
Topiocqa: Open-domain conversational question answering with topic switching V Adlakha, S Dhuliawala, K Suleman, H de Vries, S Reddy Transactions of the Association for Computational Linguistics 10, 468-483, 2022 | 94 | 2022 |
How reasonable are common-sense reasoning tasks: A case-study on the Winograd schema challenge and SWAG P Trichelair, A Emami, A Trischler, K Suleman, JCK Cheung arXiv preprint arXiv:1811.01778, 2018 | 81* | 2018 |
On the systematicity of probing contextualized word representations: The case of hypernymy in BERT A Ravichander, E Hovy, K Suleman, A Trischler, JCK Cheung Proceedings of the Ninth Joint Conference on Lexical and Computational …, 2020 | 79 | 2020 |
The KnowRef coreference corpus: Removing gender and number cues for difficult pronominal anaphora resolution A Emami, P Trichelair, A Trischler, K Suleman, H Schulz, JCK Cheung arXiv preprint arXiv:1811.01747, 2018 | 67 | 2018 |
A parallel-hierarchical model for machine comprehension on sparse data A Trischler, Z Ye, X Yuan, J He, P Bachman, K Suleman arXiv preprint arXiv:1603.08884, 2016 | 54 | 2016 |
A knowledge hunting framework for common sense reasoning A Emami, N De La Cruz, A Trischler, K Suleman, JCK Cheung arXiv preprint arXiv:1810.01375, 2018 | 43 | 2018 |
Natural language generation in dialogue using lexicalized and delexicalized data S Sharma, J He, K Suleman, H Schulz, P Bachman arXiv preprint arXiv:1606.03632, 2016 | 33 | 2016 |
Deconstructing NLG evaluation: Evaluation practices, assumptions, and their implications K Zhou, SL Blodgett, A Trischler, H Daumé III, K Suleman, A Olteanu arXiv preprint arXiv:2205.06828, 2022 | 30 | 2022 |
A generalized knowledge hunting framework for the winograd schema challenge A Emami, A Trischler, K Suleman, JCK Cheung Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 26 | 2018 |
Discovering aspects of online consumer reviews K Suleman, O Vechtomova Journal of Information Science 42 (4), 492-506, 2016 | 23 | 2016 |
An analysis of dataset overlap on winograd-style tasks A Emami, A Trischler, K Suleman, JCK Cheung arXiv preprint arXiv:2011.04767, 2020 | 21 | 2020 |
Modeling event plausibility with consistent conceptual abstraction I Porada, K Suleman, A Trischler, JCK Cheung arXiv preprint arXiv:2104.10247, 2021 | 16 | 2021 |
Layla El Asri, Mahmoud Adada, Minlie Huang, Shikhar Sharma, Wendy Tay, and Xiujun Li. 2019. Multi-domain task-completion dialog challenge S Lee, H Schulz, A Atkinson, J Gao, K Suleman Dialog System Technology Challenges 8, 0 | 16 | |
Can a gorilla ride a camel? learning semantic plausibility from text I Porada, K Suleman, JCK Cheung arXiv preprint arXiv:1911.05689, 2019 | 11 | 2019 |
Improving neural question generation using world knowledge D Gupta, K Suleman, M Adada, A McNamara, J Harris arXiv preprint arXiv:1909.03716, 2019 | 10 | 2019 |