Measuring the Structural Importance through Rhetorical Structure Index. - Narine Kokhlikyan; Alex Waibel; Yuqi Zhang; Joy Ying Zhang (HLT-NAACL, 2013)

Building Recommender Systems with PyTorch. - Dheevatsa Mudigere; Maxim Naumov; Joe Spisak; Geeta Chauhan; Narine Kokhlikyan; Amanpreet Singh; Vedanuj Goswami (KDD, 2020)

Captum: A unified and generic model interpretability library for PyTorch. - Narine Kokhlikyan; Vivek Miglani; Miguel Martin 001; Edward Wang; Bilal Alsallakh; Jonathan Reynolds; Alexander Melnikov; Natalia Kliushkina; Carlos Araya; Siqi Yan; Orion Reblitz-Richardson (CoRR, 2020)

Investigating Saturation Effects in Integrated Gradients. - Vivek Miglani; Narine Kokhlikyan; Bilal Alsallakh; Miguel Martin 001; Orion Reblitz-Richardson (CoRR, 2020)

Mind the Pad - CNNs Can Develop Blind Spots. - Bilal Alsallakh; Narine Kokhlikyan; Vivek Miglani; Jun Yuan; Orion Reblitz-Richardson (ICLR, 2021)

Fine-grained Interpretation and Causation Analysis in Deep NLP Models. - Hassan Sajjad 001; Narine Kokhlikyan; Fahim Dalvi; Nadir Durrani (CoRR, 2021)

Investigating sanity checks for saliency maps with image and text classification. - Narine Kokhlikyan; Vivek Miglani; Bilal Alsallakh; Miguel Martin 001; Orion Reblitz-Richardson (CoRR, 2021)

Method cards for prescriptive machine-learning transparency. - David Adkins; Bilal Alsallakh; Adeel Cheema; Narine Kokhlikyan; Emily McReynolds; Pushkar Mishra; Chavez Procope; Jeremy Sawruk; Erin Wang; Polina Zvyagina (CAIN, 2022)

Prescriptive and Descriptive Approaches to Machine-Learning Transparency. - David Adkins; Bilal Alsallakh; Adeel Cheema; Narine Kokhlikyan; Emily McReynolds; Pushkar Mishra; Chavez Procope; Jeremy Sawruk; Erin Wang; Polina Zvyagina (CHI Extended Abstracts, 2022)

A Tour of Visualization Techniques for Computer Vision Datasets. - Bilal Alsallakh; Pamela Bhattacharya; Vanessa Feng; Narine Kokhlikyan; Orion Reblitz-Richardson; Rahul Rajan; David Yan (CoRR, 2022)

Bias Mitigation Framework for Intersectional Subgroups in Neural Networks. - Narine Kokhlikyan; Bilal Alsallakh; Fulton Wang; Vivek Miglani; Oliver Aobo Yang; David Adkins (CoRR, 2022)

XAIR: A Framework of Explainable AI in Augmented Reality. - Xuhai Xu; Anna Yu; Tanya R. Jonker; Kashyap Todi; Feiyu Lu; Xun Qian; João Marcelo Evangelista Belo; Tianyi Wang 004; Michelle Li; Aran Mun; Te-Yen Wu; Junxiao Shen; et al. (CHI, 2023)

Mind the Pool: Convolutional Neural Networks Can Overfit Input Size. - Bilal Alsallakh; David Yan; Narine Kokhlikyan; Vivek Miglani; Orion Reblitz-Richardson; Pamela Bhattacharya (ICLR, 2023)

Error Discovery By Clustering Influence Embeddings. - Fulton Wang; Julius Adebayo; Sarah Tan; Diego Garcia-Olano; Narine Kokhlikyan (NeurIPS, 2023)

XAIR: A Framework of Explainable AI in Augmented Reality. - Xuhai Xu; Mengjie Yu; Tanya R. Jonker; Kashyap Todi; Feiyu Lu; Xun Qian; João Marcelo Evangelista Belo; Tianyi Wang 004; Michelle Li; Aran Mun; Te-Yen Wu; Junxiao Shen; et al. (CoRR, 2023)

Using Captum to Explain Generative Language Models. - Vivek Miglani; Oliver Aobo Yang; Aram H. Markosyan; Diego Garcia-Olano; Narine Kokhlikyan (CoRR, 2023)

Measuring Dejavu Memorization Efficiently. - Narine Kokhlikyan; Bargav Jayaraman; Florian Bordes; Chuan Guo 001; Kamalika Chaudhuri (NeurIPS, 2024)

Explainable Interfaces for Rapid Gaze-Based Interactions in Mixed Reality. - Mengjie Yu; Dustin Harris; Ian Jones; Ting Zhang 013; Yue Liu; Naveen Sendhilnathan; Narine Kokhlikyan; Fulton Wang; Co Tran; Jordan L. Livingston; Krista E. Taylor; Zhenhong Hu; et al. (CoRR, 2024)

On Symmetries in Convolutional Weights. - Bilal Alsallakh; Timothy Wroge; Vivek Miglani; Narine Kokhlikyan (CoRR, 2025)

Measuring Déjà vu Memorization Efficiently. - Narine Kokhlikyan; Bargav Jayaraman; Florian Bordes; Chuan Guo 001; Kamalika Chaudhuri (CoRR, 2025)

How much do language models memorize? - John X. Morris; Chawin Sitawarin; Chuan Guo 001; Narine Kokhlikyan; G. Edward Suh; Alexander M. Rush; Kamalika Chaudhuri; Saeed Mahloujifar (CoRR, 2025)