5 citations · 17 across the 13 of their papers we have counts for
8 papers · 2 filters
The Impact of Large Language Models in Academia: from Writing to Speaking
Mingmeng Geng, Caixi Chen, Yanru Wu +3
Large language models (LLMs) are increasingly impacting human society, particularly in textual information. Based on more than 30,000 papers and 1,000 presentations from machine le…
Self-Cognition in Large Language Models: An Exploratory Study
Dongping Chen, Jiawen Shi, Yao Wan +3
While Large Language Models (LLMs) have achieved remarkable success across various applications, they also raise concerns regarding self-cognition. In this paper, we perform a pion…
DataGen: Unified Synthetic Dataset Generation via Large Language Models
Yue Huang, Siyuan Wu, Chujie Gao +8
Large Language Models (LLMs) such as GPT-4 and Llama3 have significantly impacted various fields by enabling high-quality synthetic data generation and reducing dependence on expen…
Jailbreaking Large Language Models Through Alignment Vulnerabilities in Out-of-Distribution Settings
Yue Huang, Jingyu Tang, Dongping Chen +5
Recently, Large Language Models (LLMs) have garnered significant attention for their exceptional natural language processing capabilities. However, concerns about their trustworthi…
HonestLLM: Toward an Honest and Helpful Large Language Model
Chujie Gao, Siyuan Wu, Yue Huang +6
Large Language Models (LLMs) have achieved remarkable success across various industries due to their exceptional generative capabilities. However, for safe and effective real-world…
I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench
Yuan Li, Yue Huang, Yuli Lin +3
Do large language models (LLMs) exhibit any forms of awareness similar to humans? In this paper, we introduce AwareBench, a benchmark designed to evaluate awareness in LLMs. Drawin…
MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark
Dongping Chen, Ruoxi Chen, Shilin Zhang +7
Multimodal Large Language Models (MLLMs) have gained significant attention recently, showing remarkable potential in artificial general intelligence. However, assessing the utility…
LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?
Qihui Zhang, Chujie Gao, Dongping Chen +8
With the rapid development and widespread application of Large Language Models (LLMs), the use of Machine-Generated Text (MGT) has become increasingly common, bringing with it pote…