27 citations · 153 across the 63 of their papers we have counts for
6 papers · 1 filter
Leveraging Graph Diffusion Models for Network Refinement Tasks
Puja Trivedi, Ryan Rossi, David Arbour +7
Most real-world networks are noisy and incomplete samples from an unknown target distribution. Refining them by correcting corruptions or inferring unobserved regions typically imp…
TaleStream: Supporting Story Ideation with Trope Knowledge
Jean-Peïc Chou, Alexa F. Siu, Nedim Lipka +3
Story ideation is a critical part of the story-writing process. It is challenging to support computationally due to its exploratory and subjective nature. Tropes, which are recurri…
OATS: Opinion Aspect Target Sentiment Quadruple Extraction Dataset for Aspect-Based Sentiment Analysis
Siva Uday Sampreeth Chebolu, Franck Dernoncourt, Nedim Lipka +1
Aspect-based sentiment analysis (ABSA) delves into understanding sentiments specific to distinct elements within a user-generated review. It aims to analyze user-generated reviews…
Knowledge Graph Prompting for Multi-Document Question Answering
Yu Wang, Nedim Lipka, Ryan A. Rossi +3
The `pre-train, prompt, predict' paradigm of large language models (LLMs) has achieved remarkable success in open-domain question answering (OD-QA). However, few works explore this…
LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
Yanzhe Zhang, Ruiyi Zhang, Jiuxiang Gu +4
Instruction tuning unlocks the superior capability of Large Language Models (LLM) to interact with humans. Furthermore, recent instruction-following datasets include images as visu…
Envisioning the Next-Gen Document Reader
Catherine Yeh, Nedim Lipka, Franck Dernoncourt
People read digital documents on a daily basis to share, exchange, and understand information in electronic settings. However, current document readers create a static, isolated re…