35 papers
IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization
Jie Cao, Dian Jiao, Yang Dai +3
Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and personalization. The advent of large lan…
SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness
Haiyi Qiu, Kaihang Pan, Jiacheng Li +3
Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image generation. However, these m…
HeartcareGPT: A Unified Multimodal ECG Suite for Dual Signal-Image Modeling and Understanding
Yihan Xie, Sijing Li, Tianwei Lin +9
Although electrocardiograms (ECG) play a dominant role in cardiovascular diagnosis and treatment, their intrinsic data forms and representational patterns pose significant challeng…
OmniCT: Towards a Unified Slice-Volume LVLM for Comprehensive CT Analysis
Tianwei Lin, Zhongwei Qiu, Wenqiao Zhang +12
Computed Tomography (CT) is one of the most widely used and diagnostically information-dense imaging modalities, covering critical organs such as the heart, lungs, liver, and colon…
Enhancing Post-Training Quantization via Future Activation Awareness
Zheqi Lv, Zhenxuan Fan, Qi Tian +2
Post-training quantization (PTQ) is a widely used method to compress large language models (LLMs) without fine-tuning. It typically sets quantization hyperparameters (e.g., scaling…
MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient Fine-Tuning of Large Language Models
Jie Cao, Tianwei Lin, Bo Yuan +7
Recent studies integrate Low-Rank Adaptation (LoRA) and Mixture-of-Experts (MoE) to further enhance the performance of parameter-efficient fine-tuning (PEFT) methods in Large Langu…