4 papers
Self-Correcting Large Language Models: Generation vs. Multiple Choice
Hossein A. Rahmani, Satyapriya Krishna, Xi Wang +2
Large language models have recently demonstrated remarkable abilities to self-correct their responses through iterative refinement, often referred to as self-consistency or self-re…
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
Satyapriya Krishna, Tessa Han, Alex Gu +3
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of…
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation
Satyapriya Krishna, Kalpesh Krishna, Anhad Mohananey +4
Large Language Models (LLMs) have demonstrated significant performance improvements across various cognitive tasks. An emerging application is using LLMs to enhance retrieval-augme…
More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
Aaron J. Li, Satyapriya Krishna, Himabindu Lakkaraju
The trustworthiness of Large Language Models (LLMs) refers to the extent to which their outputs are reliable, safe, and ethically aligned, and it has become a crucial consideration…