| Convolution based smooth approximations to the absolute value function with application to non-smooth regularization S Voronin, G Ozkaya, D Yoshida arXiv preprint arXiv:1408.6795, 2014 | 21 | 2014 |
| Adding recurrence to pretrained transformers for improved efficiency and context size D Yoshida, A Ettinger, K Gimpel arXiv preprint arXiv:2008.07027, 2020 | 6 | 2020 |
| NF4 Isn't Information Theoretically Optimal (and that's Good) D Yoshida arXiv preprint arXiv:2306.06965, 2023 | 4 | 2023 |
| Using confusion graphs to understand classifier error D Yoshida, J Boyd-Graber Proceedings of the Workshop on Human-Computer Question Answering, 48-52, 2016 | 3 | 2016 |
| Reconsidering the past: Optimizing hidden states in language models D Yoshida, K Gimpel arXiv preprint arXiv:2112.08653, 2021 | 2 | 2021 |
| Generative Explore-Exploit: Training-free Optimization of Generative Recommender Systems using LLM Optimizers LK Senel, B Fetahu, D Yoshida, Z Chen, G Castellucci, N Vedula, J Choi, ... arXiv preprint arXiv:2406.05255, 2024 | 1 | 2024 |
| MAP's not dead yet: Uncovering true language model modes by conditioning away degeneracy D Yoshida, K Goyal, K Gimpel arXiv preprint arXiv:2311.08817, 2023 | 1 | 2023 |
| Making the Most of your Model: Methods for Finetuning and Applying Pretrained Transformers D Yoshida arXiv preprint arXiv:2408.16241, 2024 | | 2024 |
| Generative Explore-Exploit: Training-free Optimization of Generative Recommender Systems using LLM Optimizers L Kerem Senel, B Fetahu, D Yoshida, Z Chen, G Castellucci, N Vedula, ... arXiv e-prints, arXiv: 2406.05255, 2024 | | 2024 |
| Generative explore-exploit: Training-free optimization of generative recommender systems using LLM optimizers B Fetahu, Z Chen, D Yoshida, G Castellucci, N Vedula, J Choi, S Malmasi | | 2024 |
| Domain Adaptation for Factoid Question Answering D Yoshida University of Colorado at Boulder, 2017 | | 2017 |
