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cs.CL2024
RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
Junyu Luo, Xiao Luo, Kaize Ding +3
Supervised fine-tuning (SFT) plays a crucial role in adapting large language models (LLMs) to specific domains or tasks. However, as demonstrated by empirical experiments, the coll…
cs.CL2024
Political-LLM: Large Language Models in Political Science
Lincan Li, Jiaqi Li, Catherine Chen +44
In recent years, large language models (LLMs) have been widely adopted in political science tasks such as election prediction, sentiment analysis, policy impact assessment, and mis…