activity
20192023
most citedSocial network modeling and applications, a tutorial

23 citations · 44 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2023★ 2 cited

Less is More for Long Document Summary Evaluation by LLMs

Yunshu Wu, Hayate Iso, Pouya Pezeshkpour +2

Large Language Models (LLMs) have shown promising performance in summary evaluation tasks, yet they face challenges such as high computational costs and the Lost-in-the-Middle prob…

cs.CL2023★ 4 cited

Rethinking Language Models as Symbolic Knowledge Graphs

Vishwas Mruthyunjaya, Pouya Pezeshkpour, Estevam Hruschka +1

Symbolic knowledge graphs (KGs) play a pivotal role in knowledge-centric applications such as search, question answering and recommendation. As contemporary language models (LMs) t…

cs.CL2023★ 9 cited

Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions

Pouya Pezeshkpour, Estevam Hruschka

Large Language Models (LLMs) have demonstrated remarkable capabilities in various NLP tasks. However, previous works have shown these models are sensitive towards prompt wording, a…

cs.SI2023★ 23 cited

Social network modeling and applications, a tutorial

Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…

cs.DB2023★ 1 cited

Towards Multifaceted Human-Centered AI

Sajjadur Rahman, Hannah Kim, Dan Zhang +2

Human-centered AI workflows involve stakeholders with multiple roles interacting with each other and automated agents to accomplish diverse tasks. In this paper, we call for a holi…

cs.HC2023★ 2 cited

MEGAnno: Exploratory Labeling for NLP in Computational Notebooks

Dan Zhang, Hannah Kim, Rafael Li Chen +2

We present MEGAnno, a novel exploratory annotation framework designed for NLP researchers and practitioners. Unlike existing labeling tools that focus on data labeling only, our fr…

cs.CL2022★ 1 cited

Zero-shot Triplet Extraction by Template Infilling

Bosung Kim, Hayate Iso, Nikita Bhutani +3

The task of triplet extraction aims to extract pairs of entities and their corresponding relations from unstructured text. Most existing methods train an extraction model on traini…

cs.CL2021

TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration

Dongjin Choi, Sara Evensen, Çağatay Demiralp +1

Despite rapid developments in the field of machine learning research, collecting high-quality labels for supervised learning remains a bottleneck for many applications. This diffic…

cs.LG2019★ 2 cited

Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward

Daniel Severo, Flávio Amaro, Estevam R. Hruschka +1

We present a proxy dataset of vital signs with class labels indicating patient transitions from the ward to intensive care units called Ward2ICU. Patient privacy is protected using…