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20242026
most citedSora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

105 citations · 164 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search

Yanbo Wang, Zixiang Xu, Yue Huang +6

Large Language Models (LLMs) often struggle to maintain their original performance when faced with semantically coherent but task-irrelevant contextual information. Although prior…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024★ 2 cited

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…

cs.CL2024★ 54 cited

TrustLLM: Trustworthiness in Large Language Models

Yue Huang, Lichao Sun, Haoran Wang +67

Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…