4 papers
DocLens: Multi-aspect Fine-grained Evaluation for Medical Text Generation
Yiqing Xie, Sheng Zhang, Hao Cheng +6
Medical text generation aims to assist with administrative work and highlight salient information to support decision-making. To reflect the specific requirements of medical text,…
OrchestraLLM: Efficient Orchestration of Language Models for Dialogue State Tracking
Chia-Hsuan Lee, Hao Cheng, Mari Ostendorf
Large language models (LLMs) have revolutionized the landscape of Natural Language Processing systems, but are computationally expensive. To reduce the cost without sacrificing per…
GRIN: GRadient-INformed MoE
Liyuan Liu, Young Jin Kim, Shuohang Wang +14
Mixture-of-Experts (MoE) models scale more effectively than dense models due to sparse computation through expert routing, selectively activating only a small subset of expert modu…
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks
Xiaodong Yu, Hao Cheng, Xiaodong Liu +2
Despite remarkable advancements in mitigating hallucinations in large language models (LLMs) by retrieval augmentation, it remains challenging to measure the reliability of LLMs us…