4 citations · 11 across the 11 of their papers we have counts for
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cs.CL2023★ 1 cited
Unlocking Anticipatory Text Generation: A Constrained Approach for Large Language Models Decoding
Lifu Tu, Semih Yavuz, Jin Qu +4
Large Language Models (LLMs) have demonstrated a powerful ability for text generation. However, achieving optimal results with a given prompt or instruction can be challenging, esp…
cs.CL2023★ 2 cited
Investigating Answerability of LLMs for Long-Form Question Answering
Meghana Moorthy Bhat, Rui Meng, Ye Liu +2
As we embark on a new era of LLMs, it becomes increasingly crucial to understand their capabilities, limitations, and differences. Toward making further progress in this direction,…
cs.CL2023★ 4 cited
XGen-7B Technical Report
Erik Nijkamp, Tian Xie, Hiroaki Hayashi +22
Large Language Models (LLMs) have become ubiquitous across various domains, transforming the way we interact with information and conduct research. However, most high-performing LL…