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Exploring Chinese Humor Generation: A Study on Two-Part Allegorical Sayings
Humor, a culturally nuanced aspect of human language, poses challenges for computational understanding and generation, especially in Chinese humor, which remains relatively unexplored in the NLP community.
Knowledge Conflicts for LLMs: A Survey
This survey provides an in-depth analysis of knowledge conflicts for large language models (LLMs), highlighting the complex challenges they encounter when blending contextual and parametric knowledge.
Tempo: Confidentiality Preservation in Cloud-Based Neural Network Training
This paper presents Tempo, the first cloud-based deep learning system that cooperates with TEE and distributed GPUs for efficient DNN training with model confidentiality preserved.
The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation
Therefore, in this study, we delve into LLMs' susceptibility to persuasive conversations, particularly on factual questions that they can answer correctly.
