8 papers
ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning
Xianming Li, Zongxi Li, Tsz-fung Andrew Lee +3
Parameter-efficient fine-tuning (PEFT) reduces the training cost of full-parameter fine-tuning for large language models (LLMs) by training only a small set of task-specific parame…
FreqEdit: Preserving High-Frequency Features for Robust Multi-Turn Image Editing
Yucheng Liao, Jiajun Liang, Kaiqian Cui +5
Instruction-based image editing through natural language has emerged as a powerful paradigm for intuitive visual manipulation. While recent models achieve impressive results on sin…
STAR: Stepwise Task Augmentation with Relation Learning for Aspect Sentiment Quad Prediction
Wenna Lai, Haoran Xie, Guandong Xu +1
Aspect-based sentiment analysis (ABSA) aims to identify four sentiment elements, including aspect term, aspect category, opinion term, and sentiment polarity. These elements constr…
Listwise Preference Optimization with Element-wise Confusions for Aspect Sentiment Quad Prediction
Wenna Lai, Haoran Xie, Guandong Xu +2
Aspect sentiment quad prediction (ASQP) is inherently challenging to predict a structured quadruple with four core sentiment elements, including aspect term (a), aspect category (c…
When LLMs Team Up: The Emergence of Collaborative Affective Computing
Wenna Lai, Haoran Xie, Guandong Xu +2
Affective Computing (AC) is essential in bridging the gap between human emotional experiences and machine understanding. Traditionally, AC tasks in natural language processing (NLP…
ConsisLoRA: Enhancing Content and Style Consistency for LoRA-based Style Transfer
Bolin Chen, Baoquan Zhao, Haoran Xie +3
Style transfer involves transferring the style from a reference image to the content of a target image. Recent advancements in LoRA-based (Low-Rank Adaptation) methods have shown p…