58 citations · 262 across the 18 of their papers we have counts for
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cs.CL2021★ 1 cited
Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation
Yu Li, Baolin Peng, Yelong Shen +4
Knowledge-grounded dialogue systems are challenging to build due to the lack of training data and heterogeneous knowledge sources. Existing systems perform poorly on unseen topics…
cs.CL2021★ 14 cited
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation
Tianyu Liu, Yizhe Zhang, Chris Brockett +4
Large pretrained generative models like GPT-3 often suffer from hallucinating non-existent or incorrect content, which undermines their potential merits in real applications. Exist…
cs.CL2021
Finetuning Pretrained Transformers into RNNs
Jungo Kasai, Hao Peng, Yizhe Zhang +6
Transformers have outperformed recurrent neural networks (RNNs) in natural language generation. But this comes with a significant computational cost, as the attention mechanism's c…