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When Humans Leave Context Unsaid: Implicit Context as a Risk for Large Language Models
Bocheng Chen, Han Zi, Yuda Chen +6
Human language is grounded in pragmatics, necessitating implicit (extralinguistic) context to interpret language, e.g., world knowledge and social norms. However, such context is o…
Toward Global Large Language Models in Medicine
Rui Yang, Huitao Li, Weihao Xuan +48
Despite continuous advances in medical technology, the global distribution of health care resources remains uneven. The development of large language models (LLMs) has transformed…
On the Convergence of Moral Self-Correction in Large Language Models
Guangliang Liu, Haitao Mao, Bochuan Cao +4
Large Language Models (LLMs) are able to improve their responses when instructed to do so, a capability known as self-correction. When instructions provide only a general and abstr…
Smaller Large Language Models Can Do Moral Self-Correction
Guangliang Liu, Zhiyu Xue, Xitong Zhang +2
Self-correction is one of the most amazing emerging capabilities of Large Language Models (LLMs), enabling LLMs to self-modify an inappropriate output given a natural language feed…
Towards Understanding Task-agnostic Debiasing Through the Lenses of Intrinsic Bias and Forgetfulness
Guangliang Liu, Milad Afshari, Xitong Zhang +5
While task-agnostic debiasing provides notable generalizability and reduced reliance on downstream data, its impact on language modeling ability and the risk of relearning social b…
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept
Guangliang Liu, Haitao Mao, Bochuan Cao +5
Large Language Models (LLMs) are able to improve their responses when instructed to do so, a capability known as self-correction. When instructions provide only the task's goal wit…
A Survey to Recent Progress Towards Understanding In-Context Learning
Haitao Mao, Guangliang Liu, Yao Ma +3
In-Context Learning (ICL) empowers Large Language Models (LLMs) with the ability to learn from a few examples provided in the prompt, enabling downstream generalization without the…