1 |
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games ...
|
|
|
|
BASE
|
|
Show details
|
|
2 |
Seeing the world through text: Evaluating image descriptions for commonsense reasoning in machine reading comprehension ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
AutoMeTS: The Autocomplete for Medical Text Simplification. ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Part 4 - Extension Layers and Comparison to Other Formalisms ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
The Financial Narrative Summarisation Shared Task (FNS 2020) ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Automatic detection of unexpected/erroneous collocations in learner corpus ...
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Task-Aware Representation of Sentences for Generic Text Classification ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Interactive Key-Value Memory-augmented Attention for Image Paragraph Captioning ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
International Workshop on Semantic Evaluation (SemEval) ...
|
|
|
|
BASE
|
|
Show details
|
|
12 |
A Crash Course in Automatic Grammatical Error Correction 4 ...
|
|
|
|
Abstract:
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting all types of errors in written text. Although most research has focused on correcting errors in the context of English as a Second Language (ESL), GEC can also be applied to other languages and native text. The main application of a GEC system is thus to assist humans with their writing. Academic and commercial interest in GEC has grown significantly since the Helping Our Own (HOO) and Conference on Natural Language Learning (CoNLL) shared tasks in 2011-14, and a record-breaking 24 teams took part in the recent Building Educational Applications (BEA) shared task. Given this interest, and the recent shift towards neural approaches, we believe the time is right to offer a tutorial on GEC for researchers who may be new to the field or who are interested in the current state of the art and future challenges. With this in mind, the main goal of this tutorial is not only to bring attendees up to speed with GEC in general, but ...
|
|
Keyword:
Computer and Information Science; Information and Knowledge Engineering; Intelligent System; Natural Language Processing; Neural Network
|
|
URL: https://dx.doi.org/10.48448/r2aw-1479 https://underline.io/lecture/8574-a-crash-course-in-automatic-grammatical-error-correction-4
|
|
BASE
|
|
Hide details
|
|
13 |
Interactive Question Clarification in Dialogue via Reinforcement Learning ...
|
|
|
|
BASE
|
|
Show details
|
|
15 |
MaintNet: A Collaborative Open-Source Library for Predictive Maintenance Language Resources ...
|
|
|
|
BASE
|
|
Show details
|
|
16 |
A Crash Course in Automatic Grammatical Error Correction 1 ...
|
|
|
|
BASE
|
|
Show details
|
|
17 |
IDS at SemEval-2020 Task 10: Does Pre-trained Language Model Know What to Emphasize? ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|