2 citations · 3 across the 3 of their papers we have counts for
3 papers
Understanding Finetuning for Factual Knowledge Extraction
Gaurav Ghosal, Tatsunori Hashimoto, Aditi Raghunathan
In this work, we study the impact of QA fine-tuning data on downstream factuality. We show that fine-tuning on lesser-known facts that are poorly stored during pretraining yields s…
A Generalized Acquisition Function for Preference-based Reward Learning
Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell +2
Preference-based reward learning is a popular technique for teaching robots and autonomous systems how a human user wants them to perform a task. Previous works have shown that act…
Contextual Reliability: When Different Features Matter in Different Contexts
Gaurav Ghosal, Amrith Setlur, Daniel S. Brown +2
Deep neural networks often fail catastrophically by relying on spurious correlations. Most prior work assumes a clear dichotomy into spurious and reliable features; however, this i…