4 papers
DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation
Jordan Painter, Dipankar Srirag, Adarsh Kappiyath +3
Large language models increasingly understand dialectal English, yet still produce only standard, US-leaning English, leaving dialectal generation, the harder half of the problem,…
Sebra: Debiasing Through Self-Guided Bias Ranking
Adarsh Kappiyath, Abhra Chaudhuri, Ajay Jaiswal +4
Ranking samples by fine-grained estimates of spuriosity (the degree to which spurious cues are present) has recently been shown to significantly benefit bias mitigation, over the t…
DeNetDM: Debiasing by Network Depth Modulation
Silpa Vadakkeeveetil Sreelatha, Adarsh Kappiyath, Abhra Chaudhuri +1
Neural networks trained on biased datasets tend to inadvertently learn spurious correlations, hindering generalization. We formally prove that (1) samples that exhibit spurious cor…
Self-supervised Enhancement of Latent Discovery in GANs
Silpa Vadakkeeveetil Sreelatha, Adarsh Kappiyath, S Sumitra
Several methods for discovering interpretable directions in the latent space of pre-trained GANs have been proposed. Latent semantics discovered by unsupervised methods are relativ…