2 citations · 4 across the 6 of their papers we have counts for
6 papers
Assessing Model Generalization in Vicinity
Yuchi Liu, Yifan Sun, Jingdong Wang +1
This paper evaluates the generalization ability of classification models on out-of-distribution test sets without depending on ground truth labels. Common approaches often calculat…
Towards Hierarchical Multi-Agent Workflows for Zero-Shot Prompt Optimization
Yuchi Liu, Jaskirat Singh, Gaowen Liu +2
Large language models (LLMs) have shown great progress in responding to user questions, allowing for a multitude of diverse applications. Yet, the quality of LLM outputs heavily de…
Optimizing Calibration by Gaining Aware of Prediction Correctness
Yuchi Liu, Lei Wang, Yuli Zou +2
Model calibration aims to align confidence with prediction correctness. The Cross-Entropy (CE) loss is widely used for calibrator training, which enforces the model to increase con…
How to Synthesize a Large-Scale and Trainable Micro-Expression Dataset?
Yuchi Liu, Zhongdao Wang, Tom Gedeon +1
This paper does not contain technical novelty but introduces our key discoveries in a data generation protocol, a database and insights. We aim to address the lack of large-scale d…
Synthetic Data Are as Good as the Real for Association Knowledge Learning in Multi-object Tracking
Yuchi Liu, Zhongdao Wang, Xiangxin Zhou +1
Association, aiming to link bounding boxes of the same identity in a video sequence, is a central component in multi-object tracking (MOT). To train association modules, e.g., para…
Boosting Semi-Supervised Face Recognition with Noise Robustness
Yuchi Liu, Hailin Shi, Hang Du +4
Although deep face recognition benefits significantly from large-scale training data, a current bottleneck is the labelling cost. A feasible solution to this problem is semi-superv…