Results 61 to 70 of about 9,958 (247)

Generation of CCR4/CD7 Bispecific CAR‐T Cells Resistant to Fratricide and Exhaustion

Advanced Science, EarlyView.
The applications of CAR T‐cell therapy in T‐cell malignancies face limitations such as fratricide, effector‐cell exhaustion, and antigen‐escape. Herein, we developed fratricide‐ and exhaustion‐resistant CAR‐T cells that targeted CCR4 and CD7 simultaneously, with optional EGFRt safety switch. Additionally, scRNA‐seq unveiled new molecular targets, which
Sile Li, Yuanxin Li, Asif Rashid, Hong Kee Tan, Shing Chan, Man Yan Hui, Wilson Yau Ki Chan, Kee See Lam, Yinping Liu, Wenwei Tu, Wing Leung   +10 more
wiley   +1 more source

Automatic Metric Validation for Grammatical Error Correction [PDF]

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018
Metric validation in Grammatical Error Correction (GEC) is currently done by observing the correlation between human and metric-induced rankings. However, such correlation studies are costly, methodologically troublesome, and suffer from low inter-rater agreement. We propose MAEGE, an automatic methodology for GEC metric validation, that overcomes many
Leshem Choshen, Omri Abend
openaire   +2 more sources

Schooling Trajectories and the Development of Brain Dynamics: A Comparative Study of Montessori and Traditional Education

Advanced Science, EarlyView.
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua, Anira Escrichs, Yonatan Sanz Perl, Morten L. Kringelbach, Adele Diamond, Solange Denervaud, Gustavo Deco   +6 more
wiley   +1 more source

GPT-3.5 for Grammatical Error Correction

Proceedings of the Language Resources and Evaluation Conference
This paper investigates the application of GPT-3.5 for Grammatical Error Correction (GEC) in multiple languages in several settings: zero-shot GEC, fine-tuning for GEC, and using GPT-3.5 to re-rank correction hypotheses generated by other GEC models. In the zero-shot setting, we conduct automatic evaluations of the corrections proposed by GPT-3.5 using
Katinskaia Anisia, Yangarber Roman
openaire   +5 more sources

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes

Advanced Science, EarlyView.
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li, Qizhe Zhang, Hanchen Chen, Kepeng Lin, Chengfang Luo, Mengying Yang, Wei Xu, Fan Yao, Jianbing Yan, Qing‐Yong Yang, Xuehai Hu   +10 more
wiley   +1 more source

Deep Learning-Based Context-Sensitive Spelling Typing Error Correction

IEEE Access, 2020
This study aims to solve the context-sensitive spelling error problem for English documents. There are two types of spelling errors in English: non-word spelling errors and context-sensitive spelling errors. Non-word spelling errors are simple to correct
Jung-Hun Lee, Minho Kim, Hyuk-Chul Kwon
doaj   +1 more source

Grammatical Error Correction: Machine Translation and Classifiers [PDF]

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2016
We focus on two leading state-of-the-art approaches to grammatical error correction – machine learning classification and machine translation. Based on the comparative study of the two learning frameworks and through error analysis of the output of the state-of-the-art systems, we identify key strengths and weaknesses of each of these approaches and ...
Alla Rozovskaya, Dan Roth 0001
openaire   +1 more source

Nucleic Acid Therapeutics for “Undruggable” Cancer Targets: Mechanisms, Challenges, and Prospects

Advanced Science, EarlyView.
Nucleic acid therapeutics bypass the structural limitations of conventional drugs by targeting mRNA rather than proteins. This review examines how antisense oligonucleotides, siRNAs, miRNAs, aptamers, and mRNA vaccines intervene against historically undruggable oncoproteins including Ras, MYC, and p53, highlighting mechanistic advances, delivery ...
Feng Xu, Ke Wang, Kaizhong Lu, Tianlun Hou, Yuan Chen, Xian Wang, Hongchuan Jin   +6 more
wiley   +1 more source

A multi-task learning framework for efficient grammatical error correction of textual messages in mobile communications

EURASIP Journal on Wireless Communications and Networking, 2022
In mobile communications, plenty of textual messages need to be transmitted and processed rapidly. However, messages usually contain noise, which will affect the performance of related applications. Thus, we investigate grammatical error correction (GEC)
Fayu Pan, Bin Cao, Jing Fan
doaj   +1 more source

Human Evaluation of Grammatical Error Correction Systems [PDF]

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015
The paper presents the results of the first large-scale human evaluation of automatic grammatical error correction (GEC) systems. Twelve participating systems and the unchanged input of the CoNLL-2014 shared task have been reassessed in a WMT-inspired human evaluation procedure.
Grundkiewicz, Roman, Junczys-Dowmunt, Marcin, Gillian, Edward   +2 more
openaire   +2 more sources