3 citations · 6 across the 10 of their papers we have counts for
10 papers
Investigating Instruction Tuning Large Language Models on Graphs
Kerui Zhu, Bo-Wei Huang, Bowen Jin +5
Inspired by the recent advancements of Large Language Models (LLMs) in NLP tasks, there's growing interest in applying LLMs to graph-related tasks. This study delves into the capab…
Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approach
Pritom Saha Akash, Kashob Kumar Roy, Lucian Popa +1
Long-form question answering (LFQA) poses a challenge as it involves generating detailed answers in the form of paragraphs, which go beyond simple yes/no responses or short factual…
Let the Pretrained Language Models "Imagine" for Short Texts Topic Modeling
Pritom Saha Akash, Jie Huang, Kevin Chen-Chuan Chang
Topic models are one of the compelling methods for discovering latent semantics in a document collection. However, it assumes that a document has sufficient co-occurrence informati…
Text Fact Transfer
Nishant Balepur, Jie Huang, Kevin Chen-Chuan Chang
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 a…
Ask To The Point: Open-Domain Entity-Centric Question Generation
Yuxiang Liu, Jie Huang, Kevin Chen-Chuan Chang
We introduce a new task called *entity-centric question generation* (ECQG), motivated by real-world applications such as topic-specific learning, assisted reading, and fact-checkin…
Descriptive Knowledge Graph in Biomedical Domain
Kerui Zhu, Jie Huang, Kevin Chen-Chuan Chang
We present a novel system that automatically extracts and generates informative and descriptive sentences from the biomedical corpus and facilitates the efficient search for relati…