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Found 18 papers, 10 papers with code
Teaching Small Language Models to Reason
Chain of thought prompting successfully improves the reasoning capabilities of large language models, achieving state of the art results on a range of datasets.
Text Generation with Text-Editing Models
Text-editing models have recently become a prominent alternative to seq2seq models for monolingual text-generation tasks such as grammatical error correction, simplification, and style transfer.
EdiT5: Semi-Autoregressive Text-Editing with T5 Warm-Start
This is achieved by decomposing the generation process into three sub-tasks: (1) tagging to decide on the subset of input tokens to be preserved in the output, (2) re-ordering to define their order in the output text, and (3) insertion to infill the missing tokens that are not present in the input.
Controlled Text Generation as Continuous Optimization with Multiple Constraints
As large-scale language model pretraining pushes the state-of-the-art in text generation, recent work has turned to controlling attributes of the text such models generate.
A Simple Recipe for Multilingual Grammatical Error Correction
This paper presents a simple recipe to train state-of-the-art multilingual Grammatical Error Correction (GEC) models.
Ranked #1 on
Grammatical Error Correction
on Falko-MERLIN
(using extra training data)
Semantically Driven Sentence Fusion: Modeling and Evaluation
Sentence fusion is the task of joining related sentences into coherent text.
Unsupervised Text Style Transfer with Padded Masked Language Models
This allows us to identify the source tokens to delete to transform the source text to match the style of the target domain.
Rapformer: Conditional Rap Lyrics Generation with Denoising Autoencoders
The ability to combine symbols to generate language is a defining characteristic of human intelligence, particularly in the context of artistic story-telling through lyrics.
Felix: Flexible Text Editing Through Tagging and Insertion
We achieve this by decomposing the text-editing task into two sub-tasks: tagging to decide on the subset of input tokens and their order in the output text and insertion to in-fill the missing tokens in the output not present in the input.
Encode, Tag, Realize: High-Precision Text Editing
We propose LaserTagger - a sequence tagging approach that casts text generation as a text editing task.
Ranked #1 on
Sentence Fusion
on DiscoFuse
DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion
We author a set of rules for identifying a diverse set of discourse phenomena in raw text, and decomposing the text into two independent sentences.
Responsible team players wanted: an analysis of soft skill requirements in job advertisements
Our work shows that soft skills can serve as partial predictors of the gender composition in job categories and that not all soft skills receive equal wage returns at the labour market.
Learning Representations for Soft Skill Matching
The disambiguation is formulated as a binary text classification problem where the prediction is made for the potential soft skill based on the context where it occurs.
Redundancy Localization for the Conversationalization of Unstructured Responses
Conversational agents offer users a natural-language interface to accomplish tasks, entertain themselves, or access information.
Domain Adaptation for Resume Classification Using Convolutional Neural Networks
We propose a novel method for classifying resume data of job applicants into 27 different job categories using convolutional neural networks.
Automatic Prediction of Discourse Connectives
We formulate the task of discourse connective prediction and release a dataset of 2. 9M sentence pairs separated by discourse connectives for this task.
You Are What Apps You Use: Demographic Prediction Based on User's Apps
Our work addresses this need by studying the predictability of user demographics based on the list of a user's apps which is readily available to many app developers.
Social and Information Networks
DopeLearning: A Computational Approach to Rap Lyrics Generation
First, we develop a prediction model to identify the next line of existing lyrics from a set of candidate next lines.
