3 papers
cs.CL2026
Rethinking Cross-lingual Gaps from a Statistical Viewpoint
Vihari Piratla, Purvam Jain, Darshan Singh +3
Any piece of knowledge is usually expressed in one or a handful of natural languages on the web or in any large corpus. Large Language Models (LLMs) act as a bridge by acquiring kn…
cs.CL2026
XLGoBench: Detecting cross-lingual skill gaps with algorithmic tasks
Purvam Jain, Preethi Jyothi, Vihari Piratla +1
We introduce a set of synthetic algorithmic tasks to detect cross-lingual gaps in the abilities of large language models. Our benchmark is commensurate across languages, since it r…
cs.LG2025
Model Guidance via Robust Feature Attribution
Mihnea Ghitu, Vihari Piratla, Matthew Wicker
Controlling the patterns a model learns is essential to preventing reliance on irrelevant or misleading features. Such reliance on irrelevant features, often called shortcut featur…