1 citations · 1 across the 5 of their papers we have counts for
4 papers · 1 filter
Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding
Ziyao Wang, Muneeza Azmat, Ang Li +2
Large Language Models (LLMs) often excel in specific domains but fall short in others due to the limitations of their training. Thus, enabling LLMs to solve problems collaborativel…
SPRI: Aligning Large Language Models with Context-Situated Principles
Hongli Zhan, Muneeza Azmat, Raya Horesh +2
Aligning Large Language Models to integrate and reflect human values, especially for tasks that demand intricate human oversight, is arduous since it is resource-intensive and time…
Out-of-Distribution Detection using Synthetic Data Generation
Momin Abbas, Muneeza Azmat, Raya Horesh +1
Distinguishing in- and out-of-distribution (OOD) inputs is crucial for reliable deployment of classification systems. However, OOD data is typically unavailable or difficult to col…
CharED: Character-wise Ensemble Decoding for Large Language Models
Kevin Gu, Eva Tuecke, Dmitriy Katz +3
Large language models (LLMs) have shown remarkable potential for problem solving, with open source models achieving increasingly impressive performance on benchmarks measuring area…