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Found 19 papers, 10 papers with code
Near to Mid-term Risks and Opportunities of Open Source Generative AI
In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education.
Introducing v0.5 of the AI Safety Benchmark from MLCommons
We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0. 5 benchmark.
Standardize: Aligning Language Models with Expert-Defined Standards for Content Generation
Domain experts across engineering, healthcare, and education follow strict standards for producing quality content such as technical manuals, medication instructions, and children's reading materials.
Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark
We introduce Universal NER (UNER), an open, community-driven project to develop gold-standard NER benchmarks in many languages.
Ranked #1 on
Named Entity Recognition (NER)
on UNER v1 (Danish)
BasahaCorpus: An Expanded Linguistic Resource for Readability Assessment in Central Philippine Languages
Current research on automatic readability assessment (ARA) has focused on improving the performance of models in high-resource languages such as English.
CebuaNER: A New Baseline Cebuano Named Entity Recognition Model
Despite being one of the most linguistically diverse groups of countries, computational linguistics and language processing research in Southeast Asia has struggled to match the level of countries from the Global North.
Flesch or Fumble? Evaluating Readability Standard Alignment of Instruction-Tuned Language Models
Readability metrics and standards such as Flesch Kincaid Grade Level (FKGL) and the Common European Framework of Reference for Languages (CEFR) exist to guide teachers and educators to properly assess the complexity of educational materials before administering them for classroom use.
Automatic Readability Assessment for Closely Related Languages
Consequently, when both linguistic representations are combined, we achieve state-of-the-art results for Tagalog and Cebuano, and baseline scores for ARA in Bikol.
Uniform Complexity for Text Generation
Large language models (LLMs) have shown promising results in a wide array of generative NLP tasks, such as summarization and machine translation.
A Baseline Readability Model for Cebuano
In this study, we developed the first baseline readability model for the Cebuano language.
NU HLT at CMCL 2022 Shared Task: Multilingual and Crosslingual Prediction of Human Reading Behavior in Universal Language Space
In this paper, we present a unified model that works for both multilingual and crosslingual prediction of reading times of words in various languages.
Under the Microscope: Interpreting Readability Assessment Models for Filipino
Readability assessment is the process of identifying the level of ease or difficulty of a certain piece of text for its intended audience.
Diverse Linguistic Features for Assessing Reading Difficulty of Educational Filipino Texts
In order to ensure quality and effective learning, fluency, and comprehension, the proper identification of the difficulty levels of reading materials should be observed.
How Do Pedophiles Tweet? Investigating the Writing Styles and Online Personas of Child Cybersex Traffickers in the Philippines
One of the most important humanitarian responsibility of every individual is to protect the future of our children.
BERT Embeddings for Automatic Readability Assessment
Automatic readability assessment (ARA) is the task of evaluating the level of ease or difficulty of text documents for a target audience.
A Simple Post-Processing Technique for Improving Readability Assessment of Texts using Word Mover's Distance
Assessing the proper difficulty levels of reading materials or texts in general is the first step towards effective comprehension and learning.
A Simple Disaster-Related Knowledge Base for Intelligent Agents
The context-specific knowledge base developed from this study can be adapted by intelligent agents such as chat bots integrated in platforms such as Facebook Messenger for answering disaster-related queries.
Application of Lexical Features Towards Improvement of Filipino Readability Identification of Children's Literature
Proper identification of grade levels of children's reading materials is an important step towards effective learning.
Sentiment Analysis of Typhoon Related Tweets using Standard and Bidirectional Recurrent Neural Networks
The Philippines is a common ground to natural calamities like typhoons, floods, volcanic eruptions and earthquakes.
