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20152022
most citedExplanations from Large Language Models Make Small Reasoners Better

35 citations · 49 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CL2022

ZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion

Pei Chen, Wenlin Yao, Hongming Zhang +4

Knowledge base completion (KBC) aims to predict the missing links in knowledge graphs. Previous KBC tasks and approaches mainly focus on the setting where all test entities and rel…

cs.CL2022

Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer

Jianyi Zhang, Yiran Chen, Jianshu Chen

Developing neural architectures that are capable of logical reasoning has become increasingly important for a wide range of applications (e.g., natural language processing). Toward…

cs.CL2022

Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination

Yue Yang, Wenlin Yao, Hongming Zhang +3

Large-scale pretrained language models have made significant advances in solving downstream language understanding tasks. However, they generally suffer from reporting bias, the ph…

cs.CL202235 cited

Explanations from Large Language Models Make Small Reasoners Better

Shiyang Li, Jianshu Chen, Yelong Shen +9

Integrating free-text explanations to in-context learning of large language models (LLM) is shown to elicit strong reasoning capabilities along with reasonable explanations. In thi…

cs.CL2022

C-MORE: Pretraining to Answer Open-Domain Questions by Consulting Millions of References

Xiang Yue, Xiaoman Pan, Wenlin Yao +3

We consider the problem of pretraining a two-stage open-domain question answering (QA) system (retriever + reader) with strong transfer capabilities. The key challenge is how to co…

cs.CL2022

Learning-by-Narrating: Narrative Pre-Training for Zero-Shot Dialogue Comprehension

Chao Zhao, Wenlin Yao, Dian Yu +3

Comprehending a dialogue requires a model to capture diverse kinds of key information in the utterances, which are either scattered around or implicitly implied in different turns…