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20172023
most citedTranslating Pro-Drop Languages with Reconstruction Models

22 citations · 112 across the 20 of their papers we have counts for

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42 papers · 1 filter

cs.CL2023

TextBind: Multi-turn Interleaved Multimodal Instruction-following in the Wild

Huayang Li, Siheng Li, Deng Cai +5

Large language models with instruction-following abilities have revolutionized the field of artificial intelligence. These models show exceptional generalizability to tackle variou…

cs.CL2023244 cited

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Yue Zhang, Yafu Li, Leyang Cui +13

While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit h…

cs.CL20212 cited

Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction

Piji Li, Shuming Shi

We investigate the problem of Chinese Grammatical Error Correction (CGEC) and present a new framework named Tail-to-Tail (\textbf{TtT}) non-autoregressive sequence prediction to ad…

cs.CL202020 cited

TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis

Haisong Zhang, Lemao Liu, Haiyun Jiang +14

This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities. Com…

cs.CL2020

Dialogue Response Selection with Hierarchical Curriculum Learning

Yixuan Su, Deng Cai, Qingyu Zhou +6

We study the learning of a matching model for dialogue response selection. Motivated by the recent finding that models trained with random negative samples are not ideal in real-wo…

cs.CL20207 cited

Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition

Yangming Li, Lemao Liu, Shuming Shi

In many scenarios, named entity recognition (NER) models severely suffer from unlabeled entity problem, where the entities of a sentence may not be fully annotated. Through empiric…