3 papers
cs.CL2026
DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation
Jordan Painter, Dipankar Srirag, Adarsh Kappiyath +3
Large language models increasingly \emph{understand} dialectal English, yet still \emph{produce} only standard, US-leaning English, leaving dialectal generation, the harder half of…
cs.LG2025
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…
cs.LG2024
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…