Text Fact Transfer
Text style transfer is a prominent task that aims to control the style of text without inherently
changing its factual content. To cover more text modification applications, such as adapting …
changing its factual content. To cover more text modification applications, such as adapting …
KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students
Flashcard schedulers are tools that rely on 1) student models to predict the flashcards a
student knows; and 2) teaching policies to schedule cards based on these predictions …
student knows; and 2) teaching policies to schedule cards based on these predictions …
MODS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collections
Query-focused summarization (QFS) gives a summary of documents to answer a query. Past
QFS work assumes queries have one answer, ignoring debatable ones (Is law school worth …
QFS work assumes queries have one answer, ignoring debatable ones (Is law school worth …
Integrating Planning into Single-Turn Long-Form Text Generation
Generating high-quality, in-depth textual documents, such as academic papers, news
articles, Wikipedia entries, and books, remains a significant challenge for Large Language …
articles, Wikipedia entries, and books, remains a significant challenge for Large Language …
OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
Machine writing with large language models often relies on retrieval-augmented generation.
However, these approaches remain confined within the boundaries of the model's …
However, these approaches remain confined within the boundaries of the model's …
The Prompt Report: A Systematic Survey of Prompting Techniques
Generative Artificial Intelligence (GenAI) systems are being increasingly deployed across all
parts of industry and research settings. Developers and end users interact with these …
parts of industry and research settings. Developers and end users interact with these …
First Place Solution of 2023 Global Artificial Intelligence Technology Innovation Competition Track 1
X Wu, H Zhang, Y Yang, J Lu - arxiv preprint arxiv:2407.01271, 2024 - arxiv.org
In this paper, we present our champion solution to the Global Artificial Intelligence
Technology Innovation Competition Track 1: Medical Imaging Diagnosis Report Generation …
Technology Innovation Competition Track 1: Medical Imaging Diagnosis Report Generation …