| Mm1: Methods, analysis & insights from multimodal llm pre-training B McKinzie, Z Gan, JP Fauconnier, S Dodge, B Zhang, P Dufter, D Shah, ... arXiv preprint arXiv:2403.09611, 2024 | 87 | 2024 |
| Recomment: Towards critiquing-based recommendation with speech interaction P Grasch, A Felfernig, F Reinfrank Proceedings of the 7th ACM Conference on Recommender Systems, 157-164, 2013 | 62 | 2013 |
| Model stability with continuous data updates H Liu, S Patwardhan, P Grasch, S Agarwal arXiv preprint arXiv:2201.05692, 2022 | 8 | 2022 |
| Noise robust named entity understanding for voice assistants D Muralidharan, JRA Moniz, S Gao, X Yang, J Kao, S Pulman, A Kothari, ... arXiv preprint arXiv:2005.14408, 2020 | 5 | 2020 |
| On the Importance of Subtext in Recommender Systems: Eliciting Nuanced Preferences Using a Speech-based Conversational Interface P Grasch, A Felfernig i-com 14 (1), 41-52, 2015 | 3 | 2015 |
| Model Stability with Continuous Data Updates. CoRR abs/2201.05692 (2022) H Liu, PVS Avinesh, S Patwardhan, P Grasch, S Agarwal arXiv preprint arXiv:2201.05692, 2022 | 2 | 2022 |
| Noise-robust Named Entity Understanding for Virtual Assistants D Muralidharan, JRA Moniz, S Gao, X Yang, L Li, X Wang, A Patel, ... arXiv preprint arXiv:2005.14408, 2020 | 2 | 2020 |
| Understanding alignment in multimodal llms: A comprehensive study E Amirloo, JP Fauconnier, C Roesmann, C Kerl, R Boney, Y Qian, Z Wang, ... arXiv preprint arXiv:2407.02477, 2024 | 1 | 2024 |
| MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMs Y Qian, H Ye, JP Fauconnier, P Grasch, Y Yang, Z Gan arXiv preprint arXiv:2407.01509, 2024 | 1 | 2024 |
| Practical Applications of Context-Aware Computing: A Software Engineering Perspective P Grasch, DI Gerald | 1 | 2012 |
| Speech-based Recommender Systems P Grasch | | |
