24 citations · 48 across the 8 of their papers we have counts for
8 papers
Estimating the Black-box LLM Uncertainty with Distribution-Aligned Adversarial Distillation
Huizi Cui, Huan Ma, Qilin Wang +2
Large language models (LLMs) have progressed rapidly in complex reasoning and question answering, yet LLM hallucination remains a central bottleneck that hinders practical deployme…
Semantic Energy: Detecting LLM Hallucination Beyond Entropy
Huan Ma, Jiadong Pan, Jing Liu +7
Large Language Models (LLMs) are being increasingly deployed in real-world applications, but they remain susceptible to hallucinations, which produce fluent yet incorrect responses…
Estimating LLM Uncertainty with Evidence
Huan Ma, Jingdong Chen, Joey Tianyi Zhou +2
Over the past few years, Large Language Models (LLMs) have developed rapidly and are widely applied in various domains. However, LLMs face the issue of hallucinations, generating r…
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model
Huan Ma, Yan Zhu, Changqing Zhang +5
Vision-language foundation models have exhibited remarkable success across a multitude of downstream tasks due to their scalability on extensive image-text paired data. However, th…
Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning
Huan Ma, Changqing Zhang, Huazhu Fu +2
Nowadays, billions of people engage in communication and express their opinions on the internet daily. Unfortunately, not all of these expressions are friendly or compliant, making…
Attention Paper: How Generative AI Reshapes Digital Shadow Industry?
Qichao Wang, Huan Ma, Wentao Wei +8
The rapid development of digital economy has led to the emergence of various black and shadow internet industries, which pose potential risks that can be identified and managed thr…
Fairness-guided Few-shot Prompting for Large Language Models
Huan Ma, Changqing Zhang, Yatao Bian +7
Large language models have demonstrated surprising ability to perform in-context learning, i.e., these models can be directly applied to solve numerous downstream tasks by conditio…
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Huan Ma, Zongbo Han, Changqing Zhang +3
Multimodal regression is a fundamental task, which integrates the information from different sources to improve the performance of follow-up applications. However, existing methods…