Results 101 to 110 of about 36,775 (295)
Benchmarking Large Language Models in Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) is a promising approach for mitigating the hallucination of large language models (LLMs). However, existing research lacks rigorous evaluation of the impact of retrieval-augmented generation on different large ...
Lin, Hongyu +3 more
core
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
BackgroundGestational diabetes mellitus (GDM) is a prevalent chronic condition that affects maternal and fetal health outcomes worldwide, increasingly in underserved populations.
Edmund Evangelista +4 more
doaj +1 more source
Provably Secure Retrieval-Augmented Generation
Although Retrieval-Augmented Generation (RAG) systems have been widely applied, the privacy and security risks they face, such as data leakage and data poisoning, have not been systematically addressed yet. Existing defense strategies primarily rely on heuristic filtering or enhancing retriever robustness, which suffer from limited interpretability ...
Pengcheng Zhou +2 more
openaire +2 more sources
This study identifies ARID3A as a key immunosuppressive transcription factor in TNBC. Its inhibition activates the type I IFN pathway, boosting CD8+ T cell infiltration and sensitizing tumors to anti‐PD‐1. The FDA‐approved migraine drug Rimegepant targets ARID3A, enhances immunotherapy efficacy in preclinical models, and establishes a druggable axis to
Teng Zhou +12 more
wiley +1 more source
RAG-Ex: A Generic Framework for Explaining Retrieval Augmented Generation
27762780Owing to their size and complexity, large language models (LLMs) hardly explain why they generate a response. This effectively reduces the trust and confidence of end users in LLM-based applications, including Retrieval Augmented Generation (RAG)
Rudat, Max +3 more
core +2 more sources
Retrieval-Augmented Generation (RAG) pairs large language models with external search to constrain knowledge staleness and hallucination, a critical need in finance and e-commerce where numerical precision and regulatory auditability are non-negotiable ...
Pinar Ersoy, Mustafa Ersahin
doaj +1 more source
Retrieval-Augmented Text-to-Audio Generation
Accepted by ICASSP ...
Yuan, Yi +5 more
openaire +3 more sources
Corneal nerve regeneration is critical to corneal wound healing processes. The current study reveals a novel role of MG53 in promoting corneal nerve regeneration after alkali induced injury. Mechanistically, MG53 enters macrophages via its receptor, MPEG1, promotes MVP K63 ubiquitination, and triggers STAT6 induced repair‐related genes expression ...
Peng Chen +14 more
wiley +1 more source
An Agent-Based RAG Architecture for Intelligent Tourism Assistance: The Valencia Case Study
The contemporary digital landscape overwhelms visitors with fragmented and dynamic information, complicating travel planning and often leading to decision paralysis.
Andrea Bonetti +6 more
doaj +1 more source

