Search Results for author:
Found 3 papers, 2 papers with code
UniRAG: Universal Retrieval Augmentation for Multi-Modal Large Language Models
Recently, Multi-Modal(MM) Large Language Models(LLMs) have unlocked many complex use-cases that require MM understanding (e. g., image captioning or visual question answering) and MM generation (e. g., text-guided image generation or editing) capabilities.
RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!
In information retrieval, proprietary large language models (LLMs) such as GPT-4 and open-source counterparts such as LLaMA and Vicuna have played a vital role in reranking.
RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models
Researchers have successfully applied large language models (LLMs) such as ChatGPT to reranking in an information retrieval context, but to date, such work has mostly been built on proprietary models hidden behind opaque API endpoints.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
