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Found 15 papers, 3 papers with code
Social Learning: Towards Collaborative Learning with Large Language Models
We present and evaluate two approaches for knowledge transfer between LLMs.
The Impact of Preference Agreement in Reinforcement Learning from Human Feedback: A Case Study in Summarization
As a result, the task of text summarization has been identified as a good candidate for this process.
Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization
Despite recent advances, evaluating how well large language models (LLMs) follow user instructions remains an open problem.
One Size Does Not Fit All: The Case for Personalised Word Complexity Models
We use a novel active learning framework that allows models to be tailored to individuals and release a dataset of complexity annotations and models as a benchmark for further research.
On the Ethical Considerations of Text Simplification
This paper outlines the ethical implications of text simplification within the framework of assistive systems.
Word Complexity is in the Eye of the Beholder
Lexical complexity is a highly subjective notion, yet this factor is often neglected in lexical simplification and readability systems which use a {''}one-size-fits-all{''} approach.
Predicting Text Readability from Scrolling Interactions
Judging the readability of text has many important applications, for instance when performing text simplification or when sourcing reading material for language learners.
Detecting Multiword Expression Type Helps Lexical Complexity Assessment
In this work, we re-annotate the Complex Word Identification Shared Task 2018 dataset of Yimam et al. (2017), which provides complexity scores for a range of lexemes, with the types of MWEs.
Incorporating Multiword Expressions in Phrase Complexity Estimation
Multiword expressions (MWEs) were shown to be useful in a number of NLP tasks.
SeCoDa: Sense Complexity Dataset
The Sense Complexity Dataset (SeCoDa) provides a corpus that is annotated jointly for complexity and word senses.
Recursive Context-Aware Lexical Simplification
This paper presents a novel architecture for recursive context-aware lexical simplification, REC-LS, that is capable of (1) making use of the wider context when detecting the words in need of simplification and suggesting alternatives, and (2) taking previous simplification steps into account.
Comparative judgments are more consistent than binary classification for labelling word complexity
Lexical simplification systems replace complex words with simple ones based on a model of which words are complex in context.
Complex Word Identification as a Sequence Labelling Task
Complex Word Identification (CWI) is concerned with detection of words in need of simplification and is a crucial first step in a simplification pipeline.
CAMB at CWI Shared Task 2018: Complex Word Identification with Ensemble-Based Voting
This paper presents the winning systems we submitted to the Complex Word Identification Shared Task 2018.
