5 citations · 7 across the 8 of their papers we have counts for
10 papers
TCM-Eval: An Expert-Level Dynamic and Extensible Benchmark for Traditional Chinese Medicine
Zihao Cheng, Yuheng Lu, Huaiqian Ye +10
Large Language Models (LLMs) have demonstrated remarkable capabilities in modern medicine, yet their application in Traditional Chinese Medicine (TCM) remains severely limited by t…
RepoDebug: Repository-Level Multi-Task and Multi-Language Debugging Evaluation of Large Language Models
Jingjing Liu, Zeming Liu, Zihao Cheng +7
Large Language Models (LLMs) have exhibited significant proficiency in code debugging, especially in automatic program repair, which may substantially reduce the time consumption o…
TiKMiX: Take Data Influence into Dynamic Mixture for Language Model Pre-training
Yifan Wang, Binbin Liu, Fengze Liu +6
The data mixture used in the pre-training of a language model is a cornerstone of its final performance. However, a static mixing strategy is suboptimal, as the model's learning pr…
RETAIL: Towards Real-world Travel Planning for Large Language Models
Bin Deng, Yizhe Feng, Zeming Liu +5
Although large language models have enhanced automated travel planning abilities, current systems remain misaligned with real-world scenarios. First, they assume users provide expl…
ToolSpectrum : Towards Personalized Tool Utilization for Large Language Models
Zihao Cheng, Hongru Wang, Zeming Liu +4
While integrating external tools into large language models (LLMs) enhances their ability to access real-time information and domain-specific services, existing approaches focus na…
Deepfake Detection via Knowledge Injection
Tonghui Li, Yuanfang Guo, Zeming Liu +2
Deepfake detection technologies become vital because current generative AI models can generate realistic deepfakes, which may be utilized in malicious purposes. Existing deepfake d…
Generalizable AI-Generated Image Detection Based on Fractal Self-Similarity in the Spectrum
Shengpeng Xiao, Yuanfang Guo, Heqi Peng +5
With the rapid development of image synthesis techniques, AI-generated images have become increasingly realistic, which heightens the potential risk associated with their misuse an…
LSP Framework: A Compensatory Model for Defeating Trigger Reverse Engineering via Label Smoothing Poisoning
Beichen Li, Yuanfang Guo, Heqi Peng +2
Deep neural networks are vulnerable to backdoor attacks. Among the existing backdoor defense methods, trigger reverse engineering based approaches, which reconstruct the backdoor t…
AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation
Heqi Peng, Yunhong Wang, Ruijie Yang +3
Adversarial example detection, which can be conveniently applied in many scenarios, is important in the area of adversarial defense. Unfortunately, existing detection methods suffe…
Understanding Heterophily for Graph Neural Networks
Junfu Wang, Yuanfang Guo, Liang Yang +1
Graphs with heterophily have been regarded as challenging scenarios for Graph Neural Networks (GNNs), where nodes are connected with dissimilar neighbors through various patterns.…