Ailin Deng

Seeing is Believing: Mitigating Hallucination in Large Vision-language Models via CLIP-Guided Decoding

Ailin Deng , Zhirui Chen , Bryan Hooi

Reliable and Responsible Foundation Models Workshop, ICLR 2024

arxiv / code

Proximity-Informed Calibration for Deep Neural Networks

Miao Xiong , Ailin Deng , Pang Wei Koh , Jiaying Wu , Shen Li , Jianqing Xu , Bryan Hooi

NeurIPS, 2023 (Spotlight)

arxiv / code

Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection

Jiaying Wu , Shen Li , Ailin Deng , Miao Xiong , Bryan Hooi

CIKM, 2023

arxiv / code

Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement

Ailin Deng , Miao Xiong , Bryan Hooi

ICML, 2023

arxiv / code

Probabilistic Knowledge Distillation for Face Ensembles

Jianqing Xu , Shen Li , Ailin Deng , Miao Xiong , Jiaying Wu , Jiaxiang Wu , Shuohong Ding , Bryan Hooi

CVPR, 2023

pdf

Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness

Ailin Deng , Shen Li , Miao Xiong , Zhirui Chen , Bryan Hooi

ECCV, 2022

arxiv / code

Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation

Miao Xiong , Shen Li , Wenjie Feng , Ailin Deng , Jihai Zhang , Bryan Hooi

TMLR, 2022

pdf / code

CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias

Ailin Deng , Adam Goodge , Lang Yi Ang , Bryan Hooi

IJCAI, 2022

pdf / code

Graph Neural Network-Based Anomaly Detection in Multivariate Time Series

Ailin Deng , Bryan Hooi

AAAI, 2021

arxiv / code

Stars