| The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics S Gehrmann, T Adewumi, K Aggarwal, PS Ammanamanchi, ... arXiv preprint arXiv:2102.01672, 2021 | 118 | 2021 |
| Comparison of Diverse Decoding Methods from Conditional Language Models D Ippolito, R Kriz, M Kustikova, J Sedoc, C Callison-Burch arXiv preprint arXiv:1906.06362, 2019 | 99 | 2019 |
| Overview of the dialogue breakdown detection challenge 4 R Higashinaka, LF D’Haro, BA Shawar, RE Banchs, K Funakoshi, ... Increasing Naturalness and Flexibility in Spoken Dialogue Interaction: 10th …, 2021 | 82 | 2021 |
| Modeling Empathy and Distress in Reaction to News Stories S Buechel, A Buffone, B Slaff, L Ungar, J Sedoc arXiv preprint arXiv:1808.10399, 2018 | 76 | 2018 |
| ChatEval: A Tool for Chatbot Evaluation J Sedoc, D Ippolito, A Kirubarajan, J Thirani, L Ungar, C Callison-Burch Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 70 | 2019 |
| Complexity-weighted loss and diverse reranking for sentence simplification R Kriz, J Sedoc, M Apidianaki, C Zheng, G Kumar, E Miltsakaki, ... arXiv preprint arXiv:1904.02767, 2019 | 66 | 2019 |
| Natural language processing methods are sensitive to sub-clinical linguistic differences in schizophrenia spectrum disorders SX Tang, R Kriz, S Cho, SJ Park, J Harowitz, RE Gur, MT Bhati, DH Wolf, ... npj Schizophrenia 7 (1), 1-8, 2021 | 61 | 2021 |
| Continual Learning for Sentence Representations Using Conceptors T Liu, L Ungar, J Sedoc arXiv preprint arXiv:1904.09187, 2019 | 41 | 2019 |
| Health-focused conversational agents in person-centered care: a review of apps P Parmar, J Ryu, S Pandya, J Sedoc, S Agarwal NPJ digital medicine 5 (1), 1-9, 2022 | 35 | 2022 |
| Incremental Neural Coreference Resolution in Constant Memory P Xia, J Sedoc, B Van Durme Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 32 | 2020 |
| Conceptor Debiasing of Word Representations Evaluated on WEAT S Karve, L Ungar, J Sedoc arXiv preprint arXiv:1906.05993, 2019 | 32 | 2019 |
| Semantic word clusters using signed spectral clustering J Sedoc, J Gallier, D Foster, L Ungar Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 30* | 2017 |
| MimicNet: fast performance estimates for data center networks with machine learning Q Zhang, KKW Ng, C Kazer, S Yan, J Sedoc, V Liu Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 287-304, 2021 | 29 | 2021 |
| Predicting emotional word ratings using distributional representations and signed clustering J Sedoc, D Preoţiuc-Pietro, L Ungar Proceedings of the 15th Conference of the European Chapter of the …, 2017 | 25 | 2017 |
| Linear Connectivity Reveals Generalization Strategies J Juneja, R Bansal, K Cho, J Sedoc, N Saphra arXiv preprint arXiv:2205.12411, 2022 | 24 | 2022 |
| Item Response Theory for Efficient Human Evaluation of Chatbots J Sedoc, L Ungar Proceedings of the First Workshop on Evaluation and Comparison of NLP …, 2020 | 23 | 2020 |
| Automatic evaluation and moderation of open-domain dialogue systems C Zhang, J Sedoc, LF D'Haro, R Banchs, A Rudnicky arXiv preprint arXiv:2111.02110, 2021 | 22 | 2021 |
| Learning Word Ratings for Empathy and Distress from Document-Level User Responses J Sedoc, S Buechel, Y Nachmany, A Buffone, L Ungar arXiv preprint arXiv:1912.01079, 2019 | 22 | 2019 |
| Decoding Methods for Neural Narrative Generation A DeLucia, A Mueller, XL Li, J Sedoc arXiv preprint arXiv:2010.07375, 2020 | 21 | 2020 |
| Unsupervised post-processing of word vectors via conceptor negation T Liu, L Ungar, J Sedoc Proceedings of the AAAI Conference on Artificial Intelligence 33, 6778-6785, 2019 | 20 | 2019 |
Lyle UngarUniversity of PennsylvaniaVerified email at cis.upenn.edu
