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20062023
most citedSuper-resolution single-photon imaging at 8.2 kilometers

139 citations · 194 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.CL2023

UFO: Unified Fact Obtaining for Commonsense Question Answering

Zhifeng Li, Yifan Fan, Bowei Zou +1

Leveraging external knowledge to enhance the reasoning ability is crucial for commonsense question answering. However, the existing knowledge bases heavily rely on manual annotatio…

cs.CL2023

Coreference-aware Double-channel Attention Network for Multi-party Dialogue Reading Comprehension

Yanling Li, Bowei Zou, Yifan Fan +2

We tackle Multi-party Dialogue Reading Comprehension (abbr., MDRC). MDRC stands for an extractive reading comprehension task grounded on a batch of dialogues among multiple interlo…

cs.CL2023★ 1 cited

CopyNE: Better Contextual ASR by Copying Named Entities

Shilin Zhou, Zhenghua Li, Yu Hong +3

End-to-end automatic speech recognition (ASR) systems have made significant progress in general scenarios. However, it remains challenging to transcribe contextual named entities (…

cs.CL2022

Sub-Word Alignment Is Still Useful: A Vest-Pocket Method for Enhancing Low-Resource Machine Translation

Minhan Xu, Yu Hong

We leverage embedding duplication between aligned sub-words to extend the Parent-Child transfer learning method, so as to improve low-resource machine translation. We conduct exper…

cs.CL2021

DuQM: A Chinese Dataset of Linguistically Perturbed Natural Questions for Evaluating the Robustness of Question Matching Models

Hongyu Zhu, Yan Chen, Jing Yan +5

In this paper, we focus on studying robustness evaluation of Chinese question matching. Most of the previous work on analyzing robustness issue focus on just one or a few types of…

cs.CL2020★ 1 cited

DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World Applications

Hongxuan Tang, Hongyu Li, Jing Liu +3

Machine reading comprehension (MRC) is a crucial task in natural language processing and has achieved remarkable advancements. However, most of the neural MRC models are still far…