The Continuous Configuration Model: A Null for Community Detection on Weighted Networks. - John Palowitch; Shankar Bhamidi; Andrew B. Nobel (CoRR, 2016)

Significance-based community detection in weighted networks. - John Palowitch; Shankar Bhamidi; Andrew B. Nobel (J. Mach. Learn. Res., 2017)

Community Extraction in Multilayer Networks with Heterogeneous Community Structure. - James D. Wilson; John Palowitch; Shankar Bhamidi; Andrew B. Nobel (J. Mach. Learn. Res., 2017)

Testing-Based Community Detection Methods for Complex Networks. - John Palowitch (2017)

Computing the statistical significance of optimized communities in networks. - John Palowitch (CoRR, 2018)

MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit. - John Palowitch; Bryan Perozzi (CoRR, 2019)

Debiasing Graph Representations via Metadata-Orthogonal Training. - John Palowitch; Bryan Perozzi (ASONAM, 2020)

Finding Stable Groups of Cross-Correlated Features in Multi-View data. - Miheer Dewaskar; John Palowitch; Mark He; Michael I. Love; Andrew B. Nobel (CoRR, 2020)

Recurrent Graph Neural Networks for Rumor Detection in Online Forums. - Di Huang; Jacob Bartel; John Palowitch (CoRR, 2021)

GraphWorld: Fake Graphs Bring Real Insights for GNNs. - John Palowitch; Anton Tsitsulin; Brandon A. Mayer; Bryan Perozzi (KDD, 2022)

Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. - Minji Yoon; John Palowitch; Dustin Zelle; Ziniu Hu; Ruslan Salakhutdinov; Bryan Perozzi (NeurIPS, 2022)

Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. - Minji Yoon; John Palowitch; Dustin Zelle; Ziniu Hu; Ruslan Salakhutdinov; Bryan Perozzi (CoRR, 2022)

Synthetic Graph Generation to Benchmark Graph Learning. - Anton Tsitsulin; Benedek Rozemberczki; John Palowitch; Bryan Perozzi (CoRR, 2022)

TF-GNN: Graph Neural Networks in TensorFlow. - Oleksandr Ferludin; Arno Eigenwillig; Martin Blais; Dustin Zelle; Jan Pfeifer; Alvaro Sanchez-Gonzalez; Wai Lok Sibon Li; Sami Abu-El-Haija; Peter W. Battaglia; Neslihan Bulut; Jonathan Halcrow; Filipe Miguel Gonçalves de Almeida; et al. (CoRR, 2022)

Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. - Minji Yoon; Yue Wu 001; John Palowitch; Bryan Perozzi; Ruslan Salakhutdinov (CoRR, 2022)

Graph Generative Model for Benchmarking Graph Neural Networks. - Minji Yoon; Yue Wu 001; John Palowitch; Bryan Perozzi; Russ Salakhutdinov (ICML, 2023)

Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. - Mustafa Yasir; John Palowitch; Anton Tsitsulin; Long Tran-Thanh; Bryan Perozzi (CoRR, 2023)

Finding Groups of Cross-Correlated Features in Bi-View Data. - Miheer Dewaskar; John Palowitch; Mark He; Michael I. Love; Andrew B. Nobel (J. Mach. Learn. Res., 2023)

Graph Clustering with Graph Neural Networks. - Anton Tsitsulin; John Palowitch; Bryan Perozzi; Emmanuel Müller (J. Mach. Learn. Res., 2023)

Into the Unknown: Generating Geospatial Descriptions for New Environments. - Tzuf Paz-Argaman; John Palowitch; Sayali Kulkarni; Reut Tsarfaty; Jason Baldridge (ACL (Findings), 2024)

Where Do We Go From Here? Multi-scale Allocentric Relational Inferencefrom Natural Spatial Descriptions. - Tzuf Paz-Argaman; John Palowitch; Sayali Kulkarni; Jason Baldridge; Reut Tsarfaty (EACL (1), 2024)

Where Do We Go from Here? Multi-scale Allocentric Relational Inference from Natural Spatial Descriptions. - Tzuf Paz-Argaman; Sayali Kulkarni; John Palowitch; Jason Baldridge; Reut Tsarfaty (CoRR, 2024)

Towards Realistic Synthetic User-Generated Content: A Scaffolding Approach to Generating Online Discussions. - Krisztian Balog; John Palowitch; Barbara Ikica; Filip Radlinski; Hamidreza Alvari; Mehdi Manshadi (CoRR, 2024)

Entailed Between the Lines: Incorporating Implication into NLI. - Shreya Havaldar; Hamidreza Alvari; John Palowitch; Mohammad Javad Hosseini; Senaka Buthpitiya; Alex Fabrikant (ACL (1), 2025)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Lalit K. Jain; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (ACL (1), 2025)

Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning. - Bahare Fatemi; Mehran Kazemi; Anton Tsitsulin; Karishma Malkan; Jinyeong Yim; John Palowitch; Sungyong Seo; Jonathan Halcrow; Bryan Perozzi (ICLR, 2025)

SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web. - John Palowitch; Hamidreza Alvari; Mehran Kazemi; Tanvir Amin; Filip Radlinski (ICWSM, 2025)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Kshitij Jain 001; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (CoRR, 2025)

Transfer Learning for Temporal Link Prediction. - Ayan Chatterjee; Barbara Ikica; Babak Ravandi; John Palowitch (CoRR, 2025)