Simon Lupart, Stéphane Clinchant |
45th European Conference on Information Retrieval (ECIR), Dublin, Ireland, 2–6 April, 2023 |
Neural retrieval models have acquired significant effectiveness gains over the last few years compared to term-based methods. Nevertheless, those models may be brittle when faced to typos, distribution shifts or vulnerable to malicious attacks. For instance, several recent papers demonstrated that such variations severely impacted models performances, and then tried to train more resilient models. Usual approaches include synonyms replacements or typos injections — as data-augmentation — and the use of more robust tokenizers (characterBERT, BPE-dropout). To further complement the literature, we investigate in this paper adversarial training as another possible solution to this generalization issue. Our comparison includes the two main families of BERT-based neural retrievers, i.e. dense and sparse, with and without distillation techniques. We then demonstrate that one of the most simple adversarial training techniques — the Fast Gradient Sign Method (FGSM) — can improve first stage rankers robustness and effectiveness. In particular, FGSM increases models performances on both in-domain and out-of-domain distributions, and also on queries with typos, for multiple neural retrievers.
1. Difference in female/male salary: 33/40 points
2. Difference in salary increases female/male: 35/35 points
3. Salary increases upon return from maternity leave: uncalculable
4. Number of employees in under-represented gender in 10 highest salaries: 0/10 points
NAVER France targets (with respect to the 2022 index) are as follows:
En 2022, NAVER France a obtenu les notes suivantes pour chacun des indicateurs :
1. Les écarts de salaire entre les femmes et les hommes: 33 sur 40 points
2. Les écarts des augmentations individuelles entre les femmes et les hommes : 35 sur 35 points
3. Toutes les salariées augmentées revenant de congé maternité : non calculable
4. Le nombre de salarié du sexe sous-représenté parmi les 10 plus hautes rémunérations : 0 sur 10 points
Les objectifs de progression pour l’index 2022 de NAVER France sont :
NAVER LABS Europe 6-8 chemin de Maupertuis 38240 Meylan France Contact
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