4 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
Zhenbang Du, Kejing Xia, Xinrui Zhong +6
Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive generation by enabling parallel token prediction. However, practical dLLM decoding…
Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning
Zhi-Quan Feng, Ying-Jia Lin, Hung-Yu Kao
LoRA adapts large language models (LLMs) by restricting updates to low-rank subspaces of pre-trained weights. While this substantially reduces training cost, the effectiveness of a…
PromptRad: Knowledge-Enhanced Multi-Label Prompt-Tuning for Low-Resource Radiology Report Labeling
Ying-Jia Lin, Tzu-Chin Lo, Ping-Chien Li +3
Automatic report labeling facilitates the identification of clinical findings from unstructured text and enables large-scale annotation for medical imaging research. Existing rule-…
SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization
Bo-Jyun Wang, Ying-Jia Lin, Hung-Yu Kao
Small language models (SLMs), such as BART, can achieve summarization performance comparable to large language models (LLMs) via distillation. However, existing LLM-based ranking s…