activity
20202026
collaborators

8 papers

cs.LG2026

The Calls are Coming from Inside the Model: Investigating Probe-based Detection of Tool-Calling Errors in LLMs

Eric Yeats, Brendan Kennedy, Loc Truong +5

The hidden states of large language models (LLMs) are known to capture rich information relating to model knowledge and behavior that can be hard to extract from examination of inp…

cs.CV2026

What Matters in Virtual Try-Off? Dual-UNet Diffusion Model For Garment Reconstruction

Loc-Phat Truong, Meysam Madadi, Sergio Escalera

Virtual Try-On (VTON) has seen rapid advancements, providing a strong foundation for generative fashion tasks. However, the inverse problem, Virtual Try-Off (VTOFF)-aimed at recons…

cs.CV2026

MV-Fashion: Towards Enabling Virtual Try-On and Size Estimation with Multi-View Paired Data

Hunor Laczkó, Libang Jia, Loc-Phat Truong +4

Existing 4D human datasets fall short for fashion-specific research, lacking either realistic garment dynamics or task-specific annotations. Synthetic datasets suffer from a realis…

cs.LG2026

What do Geometric Hallucination Detection Metrics Actually Measure?

Eric Yeats, John Buckheit, Sarah Scullen +9

Hallucination remains a barrier to deploying generative models in high-consequence applications. This is especially true in cases where external ground truth is not readily availab…

cs.LG2022

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

Elizabeth Coda, Nico Courts, Colby Wight +6

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as ma…

cs.LG2021

Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

Loc Truong, WoongJo Choi, Colby Wight +4

Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these…

cs.CV2020

CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing

Xuanhong Chen, Bingbing Ni, Naiyuan Liu +4

In contrast to great success of memory-consuming face editing methods at a low resolution, to manipulate high-resolution (HR) facial images, i.e., typically larger than 7682 pixels…

cs.CV2020

Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers

Loc Truong, Chace Jones, Brian Hutchinson +5

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning…