activity
20212026
most citedRepresentational Alignment Supports Effective Machine Teaching

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

SciPaths: Forecasting Pathways to Scientific Discovery

Eric Chamoun, Yizhou Chi, Yulong Chen +4

Scientific progress depends on sequences of enabling contributions, yet existing AI4Science benchmarks largely focus on citation prediction, literature retrieval, or idea generatio…

cs.LG2025

Mitigating Shortcut Learning with InterpoLated Learning

Michalis Korakakis, Andreas Vlachos, Adrian Weller

Empirical risk minimization (ERM) incentivizes models to exploit shortcuts, i.e., spurious correlations between input attributes and labels that are prevalent in the majority of th…

cs.LG2024

ALVIN: Active Learning Via INterpolation

Michalis Korakakis, Andreas Vlachos, Adrian Weller

Active Learning aims to minimize annotation effort by selecting the most useful instances from a pool of unlabeled data. However, typical active learning methods overlook the prese…

cs.LG2024★ 1 cited

Representational Alignment Supports Effective Machine Teaching

Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya +11

A good teacher should not only be knowledgeable, but should also be able to communicate in a way that the student understands -- to share the student's representation of the world.…

cs.CL2021

Improving Scheduled Sampling with Elastic Weight Consolidation for Neural Machine Translation

Michalis Korakakis, Andreas Vlachos

Despite strong performance in many sequence-to-sequence tasks, autoregressive models trained with maximum likelihood estimation suffer from exposure bias, i.e. the discrepancy betw…