8 papers · 1 filter
EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Models
J. Ben Tamo, Yuxing Lu, Benoit L. Marteau +2
Large Language Models (LLMs) are fluent but prone to hallucinations, producing answers that appear plausible yet are unsupported by available evidence. This failure is especially p…
LLM-as-RNN: A Recurrent Language Model for Memory Updates and Sequence Prediction
Yuxing Lu, J. Ben Tamo, Weichen Zhao +5
Large language models are strong sequence predictors, yet standard inference relies on immutable context histories. After making an error at generation step t, the model lacks an u…
KARMA: Leveraging Multi-Agent LLMs for Automated Knowledge Graph Enrichment
Yuxing Lu, Wei Wu, Xukai Zhao +2
Maintaining comprehensive and up-to-date knowledge graphs (KGs) is critical for modern AI systems, but manual curation struggles to scale with the rapid growth of scientific litera…
MetaBench: A Multi-task Benchmark for Assessing LLMs in Metabolomics
Yuxing Lu, Xukai Zhao, J. Ben Tamo +6
Large Language Models (LLMs) have demonstrated remarkable capabilities on general text; however, their proficiency in specialized scientific domains that require deep, interconnect…
RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing
Yucheng Hu, Yuxing Lu
Large Language Models (LLMs) have catalyzed significant advancements in Natural Language Processing (NLP), yet they encounter challenges such as hallucination and the need for doma…
DoctorRAG: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients
Yuxing Lu, Gecheng Fu, Wei Wu +3
Existing medical RAG systems mainly leverage knowledge from medical knowledge bases, neglecting the crucial role of experiential knowledge derived from similar patient cases -- a k…