9 papers
TQTS-Bench: A Multi-Syntax Benchmark for Text-to-Query over Time-Series Databases
Fei Lyu, Zhiyi Peng, Jiaming Liu +5
Large language models (LLMs) have significantly advanced natural language querying over relational databases, yet their ability to query time-series databases (TSDBs) remains large…
Semantically Compatible Knowledge Distillation for Cross-Domain Object Detection with Vision Foundation Models
Qifeng Zhang, Ting Xiang, Zeyuan Bai +1
Vision foundation models (VFMs) offer strong generalization capabilities for domain-adaptive object detection (DAOD). However, existing VFM-based methods overlook the spatial-scale…
Learning-State-Aware Dynamic Generative Data Augmentation on Small-Scale Datasets
Ting Xiang, Chenxi Deng, Jinhui Zhao +4
Small-scale image classification is often limited by the scarcity of training data. Generative data augmentation (GDA) based on pretrained generative models has emerged as an effec…
Human-Guided Causal Knowledge Injection for Virtual Cells
Pengcheng Wang, Changjian Chen, Zhuo Tang +4
Virtual cells employ machine learning models to simulate and predict cellular behaviors, serving as a critical computational framework for investigating health and disease. Injecti…
CausalTAD: Injecting Causal Knowledge into Large Language Models for Tabular Anomaly Detection
Ruiqi Wang, Ruikang Liu, Runyu Chen +4
Detecting anomalies in tabular data is critical for many real-world applications, such as credit card fraud detection. With the rapid advancements in large language models (LLMs),…
Invisible Clean-Label Backdoor Attacks for Generative Data Augmentation
Ting Xiang, Jinhui Zhao, Changjian Chen +1
With the rapid advancement of image generative models, generative data augmentation has become an effective way to enrich training images, especially when only small-scale datasets…
Enhancing Small-Scale Dataset Expansion with Triplet-Connection-based Sample Re-Weighting
Ting Xiang, Changjian Chen, Zhuo Tang +5
The performance of computer vision models in certain real-world applications, such as medical diagnosis, is often limited by the scarcity of available images. Expanding datasets us…
Interactive Hybrid Rice Breeding with Parametric Dual Projection
Changjian Chen, Pengcheng Wang, Fei Lyu +6
Hybrid rice breeding crossbreeds different rice lines and cultivates the resulting hybrids in fields to select those with desirable agronomic traits, such as higher yields. Recentl…
Human-Guided Image Generation for Expanding Small-Scale Training Image Datasets
Changjian Chen, Fei Lv, Yalong Guan +4
The performance of computer vision models in certain real-world applications (e.g., rare wildlife observation) is limited by the small number of available images. Expanding dataset…