1 citations · 1 across the 3 of their papers we have counts for
3 papers
Can LLMs get help from other LLMs without revealing private information?
Florian Hartmann, Duc-Hieu Tran, Peter Kairouz +2
Cascades are a common type of machine learning systems in which a large, remote model can be queried if a local model is not able to accurately label a user's data by itself. Servi…
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs
Victor Carbune, Hassan Mansoor, Fangyu Liu +4
Vision-language models (VLMs) are achieving increasingly strong performance on multimodal tasks. However, reasoning capabilities remain limited particularly for smaller VLMs, while…
Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization
Ondrej Skopek, Rahul Aralikatte, Sian Gooding +1
Despite recent advances, evaluating how well large language models (LLMs) follow user instructions remains an open problem. While evaluation methods of language models have seen a…