6 papers
Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation
Adam Fisch, Joshua Maynez, R. Alex Hofer +3
Prediction-powered inference (PPI) is a method that improves statistical estimates based on limited human-labeled data. PPI achieves this by combining small amounts of human-labele…
Language and Task Arithmetic with Parameter-Efficient Layers for Zero-Shot Summarization
Alexandra Chronopoulou, Jonas Pfeiffer, Joshua Maynez +3
Parameter-efficient fine-tuning (PEFT) using labeled task data can significantly improve the performance of large language models (LLMs) on the downstream task. However, there are…
Learning to Plan and Generate Text with Citations
Constanza Fierro, Reinald Kim Amplayo, Fantine Huot +4
The increasing demand for the deployment of LLMs in information-seeking scenarios has spurred efforts in creating verifiable systems, which generate responses to queries along with…
Bayesian Prediction-Powered Inference
R. Alex Hofer, Joshua Maynez, Bhuwan Dhingra +3
Prediction-powered inference (PPI) is a method that improves statistical estimates based on limited human-labeled data. Specifically, PPI methods provide tighter confidence interva…
Naive Bayes-based Context Extension for Large Language Models
Jianlin Su, Murtadha Ahmed, Wenbo +3
Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations…
PLAN: Summarizing using a Content Plan as Cross-Lingual Bridge
Fantine Huot, Joshua Maynez, Chris Alberti +5
Cross-lingual summarization consists of generating a summary in one language given an input document in a different language, allowing for the dissemination of relevant content acr…