22 citations · 23 across the 4 of their papers we have counts for
4 papers
Does Prompt Formatting Have Any Impact on LLM Performance?
Jia He, Mukund Rungta, David Koleczek +3
In the realm of Large Language Models (LLMs), prompt optimization is crucial for model performance. Although previous research has explored aspects like rephrasing prompt contexts,…
Alternate Preference Optimization for Unlearning Factual Knowledge in Large Language Models
Anmol Mekala, Vineeth Dorna, Shreya Dubey +5
Machine unlearning aims to efficiently eliminate the influence of specific training data, known as the forget set, from the model. However, existing unlearning methods for Large La…
UMass PCL at SemEval-2022 Task 4: Pre-trained Language Model Ensembles for Detecting Patronizing and Condescending Language
David Koleczek, Alex Scarlatos, Siddha Karakare +1
Patronizing and condescending language (PCL) is everywhere, but rarely is the focus on its use by media towards vulnerable communities. Accurately detecting PCL of this form is a d…
On Optimizing Interventions in Shared Autonomy
Weihao Tan, David Koleczek, Siddhant Pradhan +7
Shared autonomy refers to approaches for enabling an autonomous agent to collaborate with a human with the aim of improving human performance. However, besides improving performanc…