23 citations · 44 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
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…
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…