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cs.CL2025
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models
Youan Cong, Pritom Saha Akash, Cheng Wang +1
We introduce the \textit{Extract-Refine-Retrieve-Read} (ERRR) framework, a novel approach designed to bridge the pre-retrieval information gap in Retrieval-Augmented Generation (RA…
cs.CL2024
Calibrating Verbalized Probabilities for Large Language Models
Cheng Wang, Gyuri Szarvas, Georges Balazs +2
Calibrating verbalized probabilities presents a novel approach for reliably assessing and leveraging outputs from black-box Large Language Models (LLMs). Recent methods have demons…
cs.CL2024
TRACE: TRansformer-based Attribution using Contrastive Embeddings in LLMs
Cheng Wang, Xinyang Lu, See-Kiong Ng +1
The rapid evolution of large language models (LLMs) represents a substantial leap forward in natural language understanding and generation. However, alongside these advancements co…