activity
20232025
most citedEstimating LLM Uncertainty with Evidence

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG2025

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…

cs.CL2025

Computational Reasoning of Large Language Models

Haitao Wu, Zongbo Han, Joey Tianyi Zhou +2

With the rapid development and widespread application of Large Language Models (LLMs), multidimensional evaluation has become increasingly critical. However, current evaluations ar…

cs.CL2025

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…

cs.CV2024

Evolving from Single-modal to Multi-modal Facial Deepfake Detection: Progress and Challenges

Ping Liu, Qiqi Tao, Joey Tianyi Zhou

As synthetic media, including video, audio, and text, become increasingly indistinguishable from real content, the risks of misinformation, identity fraud, and social manipulation…

cs.LG2024

Selective Learning: Towards Robust Calibration with Dynamic Regularization

Zongbo Han, Yifeng Yang, Changqing Zhang +3

Miscalibration in deep learning refers to there is a discrepancy between the predicted confidence and performance. This problem usually arises due to the overfitting problem, which…

cs.LG2024

Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching

Tianle Zhang, Yuchen Zhang, Kun Wang +7

Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have raised growing concerns. As one of the most promising…