| FiLM: Visual Reasoning with a General Conditioning Layer E Perez, F Strub, H De Vries, V Dumoulin, A Courville AAAI 2018, 2018 | 1104* | 2018 |
| Retrieval-augmented generation for knowledge-intensive nlp tasks P Lewis, E Perez, A Piktus, F Petroni, V Karpukhin, N Goyal, H Küttler, ... NeurIPS 2020, 2020 | 480 | 2020 |
| Eli5: Long form question answering A Fan, Y Jernite*, E Perez*, D Grangier, J Weston, M Auli Association for Computational Linguistics (ACL) 2019, 2019 | 169 | 2019 |
| Feature-wise transformations V Dumoulin, E Perez, N Schucher, F Strub, H Vries, A Courville, Y Bengio Distill 3 (7), e11, 2018 | 127* | 2018 |
| Supervised multimodal bitransformers for classifying images and text D Kiela, S Bhooshan, H Firooz, E Perez, D Testuggine arXiv preprint arXiv:1909.02950, 2019 | 116 | 2019 |
| HoME: a Household Multimodal Environment S Brodeur, E Perez*, A Anand*, F Golemo*, L Celotti, F Strub, J Rouat, ... ICLR 2018 Workshop, 2017 | 116 | 2017 |
| True Few-Shot Learning with Language Models E Perez, D Kiela, K Cho NeurIPS 2021, 2021 | 113 | 2021 |
| Unsupervised Question Decomposition for Question Answering E Perez, P Lewis, W Yih, K Cho, D Kiela EMNLP 2020, 2020 | 83 | 2020 |
| Learning Visual Reasoning Without Strong Priors E Perez, H De Vries, F Strub, V Dumoulin, A Courville ICML 2017 Workshop, 2017 | 65 | 2017 |
| Red teaming language models with language models E Perez, S Huang, F Song, T Cai, R Ring, J Aslanides, A Glaese, ... EMNLP 2022, 2022 | 26 | 2022 |
| Finding Generalizable Evidence by Learning to Convince Q&A Models E Perez, S Karamcheti, R Fergus, J Weston, D Kiela, K Cho EMNLP 2019, 2019 | 25 | 2019 |
| Visual Reasoning with Multi-hop Feature Modulation F Strub, M Seurin, E Perez, H De Vries, J Mary, P Preux, A Courville, ... Proceedings of the European Conference on Computer Vision (ECCV), 784-800, 2018 | 24* | 2018 |
| Case-based reasoning for natural language queries over knowledge bases R Das, M Zaheer, D Thai, A Godbole, E Perez, JY Lee, L Tan, ... EMNLP 2021, 2021 | 11 | 2021 |
| Semi-supervised learning with the deep rendering mixture model T Nguyen, W Liu, E Perez, RG Baraniuk, AB Patel arXiv preprint arXiv:1612.01942, 2016 | 11 | 2016 |
| Rissanen data analysis: Examining dataset characteristics via description length E Perez, D Kiela, K Cho ICML 2021, 2021 | 10 | 2021 |
| Training Language Models with Language Feedback J Scheurer, JA Campos, JS Chan, A Chen, K Cho, E Perez ACL 2022 Workshop on Learning with Natural Language Supervision, 0 | 5* | |
| Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions A Parrish*, H Trivedi*, E Perez*, A Chen, N Nangia, J Phang, SR Bowman ACL 2022 Workshop on Learning with Natural Language Supervision, 2022 | 3 | 2022 |
| Language models (mostly) know what they know S Kadavath, T Conerly, A Askell, T Henighan, D Drain, E Perez, ... arXiv preprint arXiv:2207.05221, 2022 | 2 | 2022 |
| Few-shot adaptation works with unpredictable data JS Chan, M Pieler, J Jao, J Scheurer, E Perez arXiv preprint arXiv:2208.01009, 2022 | 1 | 2022 |
| RL with KL penalties is better viewed as Bayesian inference T Korbak, E Perez, CL Buckley EMNLP 2022, 2022 | 1 | 2022 |
Florian STRUBDeepMindVerified email at google.com
