Mental models of AI agents in a cooperative game setting KI Gero, Z Ashktorab, C Dugan, Q Pan, J Johnson, W Geyer, M Ruiz, ... Proceedings of the 2020 chi conference on human factors in computing systems …, 2020 | 103 | 2020 |
Beyond backprop: Online alternating minimization with auxiliary variables A Choromanska, B Cowen, S Kumaravel, R Luss, M Rigotti, I Rish, ... International Conference on Machine Learning, 1193-1202, 2019 | 70 | 2019 |
Text-based rl agents with commonsense knowledge: New challenges, environments and baselines K Murugesan, M Atzeni, P Kapanipathi, P Shukla, S Kumaravel, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 9018-9027, 2021 | 58 | 2021 |
Human-ai collaboration in a cooperative game setting: Measuring social perception and outcomes Z Ashktorab, QV Liao, C Dugan, J Johnson, Q Pan, W Zhang, ... Proceedings of the ACM on Human-Computer Interaction 4 (CSCW2), 1-20, 2020 | 53 | 2020 |
Effects of communication directionality and AI agent differences in human-AI interaction Z Ashktorab, C Dugan, J Johnson, Q Pan, W Zhang, S Kumaravel, ... Proceedings of the 2021 CHI conference on human factors in computing systems …, 2021 | 30 | 2021 |
Proceedings of the 2021 CHI conference on human factors in computing systems Z Ashktorab, C Dugan, J Johnson, Q Pan, W Zhang, S Kumaravel, ... Association for Computing Machinery,, 2021 | 19 | 2021 |
Beyond backprop: Alternating minimization with co-activation memory A Choromanska, E Tandon, S Kumaravel, R Luss, I Rish, B Kingsbury, ... stat 1050, 24, 2018 | 12 | 2018 |
Mental Models of AI Agents in a Cooperative Game Setting. Association for Computing Machinery, New York, NY, USA, 1–12 KI Gero, Z Ashktorab, C Dugan, Q Pan, J Johnson, W Geyer, M Ruiz, ... | 6 | 2020 |
DocAMR: Multi-sentence AMR representation and evaluation T Naseem, A Blodgett, S Kumaravel, T O'Gorman, YS Lee, J Flanigan, ... arXiv preprint arXiv:2112.08513, 2021 | 4 | 2021 |
Cross sentence inference for process knowledge S Louvan, C Naik, S Kumaravel, H Kwon, N Balasubramanian, P Clark Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 4 | 2016 |
Formally specifying the high-level behavior of LLM-based agents M Crouse, I Abdelaziz, K Basu, S Dan, S Kumaravel, A Fokoue, ... arXiv preprint arXiv:2310.08535, 2023 | 3 | 2023 |
Word embedding quality assessment through asymmetry W Zhang, Y Yu, MS Campbell, S Kumaravel US Patent App. 17/005,471, 2022 | 1 | 2022 |
CHRONOS: A Schema-Based Event Understanding and Prediction System M Chang, A Fokoue, R Uceda-Sosa, P Awasthy, K Barker, S Kumaravel, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (21), 22871 …, 2024 | | 2024 |
API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs K Basu, I Abdelaziz, S Chaudhury, S Dan, M Crouse, A Munawar, ... arXiv preprint arXiv:2402.15491, 2024 | | 2024 |
Slide, Constrain, Parse, Repeat: Synchronous SlidingWindows for Document AMR Parsing S Kumaravel, T Naseem, RF Astudillo, R Florian, S Roukos arXiv preprint arXiv:2305.17273, 2023 | | 2023 |
Random Action Replay for Reinforcement Learning W Zhang, MS Campbell, Y Yu, S Kumaravel US Patent App. 16/946,586, 2021 | | 2021 |
Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning W Zhang, M Campbell, Y Yu, S Kumaravel Proceedings of the AAAI Conference on Artificial Intelligence 35 (16), 14472 …, 2021 | | 2021 |
Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning W Zhang, M Campbell, Y Yu, S Kumaravel arXiv preprint arXiv:2012.01631, 2020 | | 2020 |