4 citations · 9 across the 9 of their papers we have counts for
4 papers · 1 filter
Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
Qitan Lv, Jie Wang, Hanzhu Chen +3
Generation of plausible but incorrect factual information, often termed hallucination, has attracted significant research interest. Retrieval-augmented language model (RALM) -- whi…
SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs
Hanzhu Chen, Xu Shen, Qitan Lv +3
Knowledge graphs (KGs) play a pivotal role in knowledge-intensive tasks across specialized domains, where the acquisition of precise and dependable knowledge is crucial. However, e…
Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction
Tianyu Liu, Qitan Lv, Jie Wang +2
Inductive relation prediction (IRP) -- where entities can be different during training and inference -- has shown great power for completing evolving knowledge graphs. Existing wor…
PEARL: Parallel Speculative Decoding with Adaptive Draft Length
Tianyu Liu, Yun Li, Qitan Lv +4
Speculative decoding (SD), where an extra draft model is employed to provide multiple draft tokens first, and then the original target model verifies these tokens in parallel, has…