Use title and abstract to predict future academic impact
Analyze similarity of patent claims and responses
Rerank documents based on a query
Display and filter LLM benchmark results
Search for similar AI-generated patent abstracts
Identify AI-generated text
Analyze Ancient Greek text for syntax and named entities
Upload a PDF or TXT, ask questions about it
Experiment with and compare different tokenizers
Classify patent abstracts into subsectors
Explore Arabic NLP tools
Generative Tasks Evaluation of Arabic LLMs
Extract relationships and entities from text
Newborn Article Impact Predict is a text analysis tool designed to predict the future academic impact of scholarly articles based on their title and abstract. This tool leverages advanced AI technology to analyze the content and provide insights into how an article might be received in the academic community.
What makes Newborn Article Impact Predict accurate?
The tool uses advanced AI models trained on a vast dataset of academic articles and their citation histories to ensure accurate predictions.
Can the tool support languages other than English?
Currently, the tool primarily supports English, but there are plans to expand to other languages in future updates.
How does the prediction model determine academic impact?
The model analyzes factors such as keyword relevance, content novelty, and language clarity to estimate potential impact.