4 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
KALE: Enhancing Knowledge Manipulation in Large Language Models via Knowledge-aware Learning
Qitan Lv, Tianyu Liu, Qiaosheng Zhang +2
Despite the impressive performance of large language models (LLMs) pretrained on vast knowledge corpora, advancing their knowledge manipulation-the ability to effectively recall, r…
TALON: Confidence-Aware Speculative Decoding with Adaptive Token Trees
Tianyu Liu, Qitan Lv, Yuhao Shen +2
Speculative decoding (SD) has become a standard technique for accelerating LLM inference without sacrificing output quality. Recent advances in speculative decoding have shifted fr…
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…
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…