Publications (13)
CoIDO: Efficient Data Selection for Visual Instruction Tuning via Coupled Importance-Diversity Optimization
Yichen Yan, Ming Zhong, Qi Zhu +3
Multimodal large language models (MLLMs) rely heavily on instruction tuning to align vision and language capabilities, yet the computational cost of training on large-scale dataset…
Target Aggregate Data Adjustment Method for Transportability Analysis Utilizing Summary-Level Data from the Target Population
Yichen Yan, Quang Vuong, Rebecca K Metcalfe +3
Transportability analysis is a causal inference framework used to evaluate the external validity of randomized clinical trials (RCTs) or observational studies. Most existing transp…
Self-adaptive Dataset Construction for Real-World Multimodal Safety Scenarios
Jingen Qu, Lijun Li, Bo Zhang +2
Multimodal large language models (MLLMs) are rapidly evolving, presenting increasingly complex safety challenges. However, current dataset construction methods, which are risk-orie…
Beyond Literal Descriptions: Understanding and Locating Open-World Objects Aligned with Human Intentions
Wenxuan Wang, Yisi Zhang, Xingjian He +4
Visual grounding (VG) aims at locating the foreground entities that match the given natural language expressions. Previous datasets and methods for classic VG task mainly rely on t…
Fuse & Calibrate: A bi-directional Vision-Language Guided Framework for Referring Image Segmentation
Yichen Yan, Xingjian He, Sihan Chen +2
Referring Image Segmentation (RIS) aims to segment an object described in natural language from an image, with the main challenge being a text-to-pixel correlation. Previous method…
Calibration & Reconstruction: Deep Integrated Language for Referring Image Segmentation
Yichen Yan, Xingjian He, Sihan Chen +1
Referring image segmentation aims to segment an object referred to by natural language expression from an image. The primary challenge lies in the efficient propagation of fine-gra…
Towards Efficient Data-flow Test Data Generation
Ting Su, Chengyu Zhang, Yichen Yan +5
Data-flow testing (DFT) aims to detect potential data interaction anomalies by focusing on the points at which variables receive values and the points at which these values are use…
MMNet: Multi-Mask Network for Referring Image Segmentation
Yichen Yan, Xingjian He, Wenxuan Wan +1
Referring image segmentation aims to segment an object referred to by natural language expression from an image. However, this task is challenging due to the distinct data properti…
Comparison of Simulation-Guided Design to Closed-Form Power Calculations in Planning a Cluster Randomized Trial with Covariate-Constrained Randomization: A Case Study in Rural Chad
Jay JH Park, Rebecca K. Metcalfe, Nathaniel Dyrkton +5
Current practices for designing cluster-randomized trials (cRCTs) typically rely on closed-form formulas for power calculations. For cRCTs using covariate-constrained randomization…
EAVL: Explicitly Align Vision and Language for Referring Image Segmentation
Yichen Yan, Xingjian He, Wenxuan Wang +2
Referring image segmentation (RIS) aims to segment an object mentioned in natural language from an image. The main challenge is text-to-pixel fine-grained correlation. In the previ…
Fully Automated Functional Fuzzing of Android Apps for Detecting Non-crashing Logic Bugs
Ting Su, Yichen Yan, Jue Wang +5
Android apps are GUI-based event-driven software and have become ubiquitous in recent years. Obviously, functional correctness is critical for an app's success. However, in additio…
SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry
Chengyu Zhang, Yichen Yan, Hanru Zhou +5
In this paper, we aim at the automated unit coverage-based testing for embedded software. To achieve the goal, by analyzing the industrial requirements and our previous work on aut…
Presentation Proposal: Towards Efficient Data-flow Test Data Generation Using KLEE
Chengyu Zhang, Ting Su, Yichen Yan +2
Dataflow coverage, one of the white-box testing criteria, focuses on the relations between variable definitions and their uses.Several empirical studies have proved data-flow testi…