1 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
Pay for The Second-Best Service: A Game-Theoretic Approach Against Dishonest LLM Providers
Yuhan Cao, Yu Wang, Sitong Liu +3
The widespread adoption of Large Language Models (LLMs) through Application Programming Interfaces (APIs) induces a critical vulnerability: the potential for dishonest manipulation…
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
Yu Wang, Yijian Liu, Liheng Ji +11
We build \textbf{AICrypto}, a comprehensive benchmark designed to evaluate the cryptography capabilities of large language models (LLMs). The benchmark comprises 135 multiple-choic…
Demonstrations of Integrity Attacks in Multi-Agent Systems
Can Zheng, Yuhan Cao, Xiaoning Dong +1
Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding, code generation, and complex planning. Simultaneously, Multi-Agent Systems…
Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
Yuhan Cao, Zian Chen, Kun Quan +17
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, capable of tackling complex tasks during inference. However, the extent to which LLMs can…
SC-LoRA: Balancing Efficient Fine-tuning and Knowledge Preservation via Subspace-Constrained LoRA
Minrui Luo, Fuhang Kuang, Yu Wang +2
Parameter-Efficient Fine-Tuning (PEFT) methods, particularly Low-Rank Adaptation (LoRA), are indispensable for efficiently customizing Large Language Models (LLMs). However, vanill…