Search Results for author:
Found 7 papers, 3 papers with code
Authorship Obfuscation in Multilingual Machine-Generated Text Detection
However, it is susceptible to authorship obfuscation (AO) methods, such as paraphrasing, which can cause MGTs to evade detection.
Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation
Recent ubiquity and disruptive impacts of large language models (LLMs) have raised concerns about their potential to be misused (. i. e, generating large-scale harmful and misleading content).
MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark
There is a lack of research into capabilities of recent LLMs to generate convincing text in languages other than English and into performance of detectors of machine-generated text in multilingual settings.
JAMES: Normalizing Job Titles with Multi-Aspect Graph Embeddings and Reasoning
In online job marketplaces, it is important to establish a well-defined job title taxonomy for various downstream tasks (e. g., job recommendation, users' career analysis, and turnover prediction).
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
Due to the nature of mathematical texts, which often use domain specific vocabulary along with equations and math symbols, we posit that the development of a new BERT model for mathematics would be useful for many mathematical downstream tasks.
Classifying Math KCs via Task-Adaptive Pre-Trained BERT
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers.
A Comparison of Entity Matching Methods between English and Japanese Katakana
We built two research questions to clarify which types of entity matching systems works better than others.
