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cs.CL2024
Evaluating LLMs' Divergent Thinking Capabilities for Scientific Idea Generation with Minimal Context
Kai Ruan, Xuan Wang, Jixiang Hong +3
While Large Language Models (LLMs) demonstrate remarkable capabilities in scientific tasks such as literature analysis and experimental design (e.g., accurately extracting key find…
cs.CL2023
CycleAlign: Iterative Distillation from Black-box LLM to White-box Models for Better Human Alignment
Jixiang Hong, Quan Tu, Changyu Chen +3
Language models trained on large-scale corpus often generate content that is harmful, toxic, or contrary to human preferences, making their alignment with human values a critical c…