4 citations · 7 across the 4 of their papers we have counts for
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cs.CL2024
Learning to Trust Your Feelings: Leveraging Self-awareness in LLMs for Hallucination Mitigation
Yuxin Liang, Zhuoyang Song, Hao Wang +1
We evaluate the ability of Large Language Models (LLMs) to discern and express their internal knowledge state, a key factor in countering factual hallucination and ensuring reliabl…
cs.CL2023★ 4 cited
AcademicGPT: Empowering Academic Research
Shufa Wei, Xiaolong Xu, Xianbiao Qi +21
Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, g…
cs.CL2023★ 3 cited
Never Lost in the Middle: Mastering Long-Context Question Answering with Position-Agnostic Decompositional Training
Junqing He, Kunhao Pan, Xiaoqun Dong +7
While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts. The "lost in the…