Disentangled representations via synergy minimization. - Greg Ver Steeg; Rob Brekelmans; Hrayr Harutyunyan; Aram Galstyan (Allerton, 2017)

Multitask Learning and Benchmarking with Clinical Time Series Data. - Hrayr Harutyunyan; Hrant Khachatrian; David C. Kale; Aram Galstyan (CoRR, 2017)

MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. - Sami Abu-El-Haija; Bryan Perozzi; Amol Kapoor; Nazanin Alipourfard; Kristina Lerman; Hrayr Harutyunyan; Greg Ver Steeg; Aram Galstyan (ICML, 2019)

Fast structure learning with modular regularization. - Greg Ver Steeg; Hrayr Harutyunyan; Daniel Moyer; Aram Galstyan (NeurIPS, 2019)

Efficient Covariance Estimation from Temporal Data. - Hrayr Harutyunyan; Daniel Moyer; Hrant Khachatrian; Greg Ver Steeg; Aram Galstyan (CoRR, 2019)

Improving generalization by controlling label-noise information in neural network weights. - Hrayr Harutyunyan; Kyle Reing; Greg Ver Steeg; Aram Galstyan (ICML, 2020)

Estimating informativeness of samples with Smooth Unique Information. - Hrayr Harutyunyan; Alessandro Achille; Giovanni Paolini; Orchid Majumder; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ICLR, 2021)

Information-theoretic generalization bounds for black-box learning algorithms. - Hrayr Harutyunyan; Maxim Raginsky; Greg Ver Steeg; Aram Galstyan (NeurIPS, 2021)

Failure Modes of Domain Generalization Algorithms. - Tigran Galstyan; Hrayr Harutyunyan; Hrant Khachatrian; Greg Ver Steeg; Aram Galstyan (CVPR, 2022)

Formal limitations of sample-wise information-theoretic generalization bounds. - Hrayr Harutyunyan; Greg Ver Steeg; Aram Galstyan (ITW, 2022)

Identifying geopolitical event precursors using attention-based LSTMs. - K. S. M. Tozammel Hossain; Hrayr Harutyunyan; Yue Ning 001; Brendan Kennedy 001; Naren Ramakrishnan; Aram Galstyan (Frontiers Artif. Intell., 2022)

A Meta-Learning Approach to Predicting Performance and Data Requirements. - Achin Jain; Gurumurthy Swaminathan; Paolo Favaro; Hao Yang 043; Avinash Ravichandran; Hrayr Harutyunyan; Alessandro Achille; Onkar Dabeer; Bernt Schiele; Ashwin Swaminathan; Stefano Soatto (CVPR, 2023)

Supervision Complexity and its Role in Knowledge Distillation. - Hrayr Harutyunyan; Ankit Singh Rawat; Aditya Krishna Menon; Seungyeon Kim 001; Sanjiv Kumar (ICLR, 2023)

Identifying and Disentangling Spurious Features in Pretrained Image Representations. - Rafayel Darbinyan; Hrayr Harutyunyan; Aram H. Markosyan; Hrant Khachatrian (CoRR, 2023)

On information captured by neural networks: connections with memorization and generalization. - Hrayr Harutyunyan (CoRR, 2023)

In-context Learning in Presence of Spurious Correlations. - Hrayr Harutyunyan; Rafayel Darbinyan; Samvel Karapetyan; Hrant Khachatrian (CoRR, 2024)

Mimetic Initialization Helps State Space Models Learn to Recall. - Asher Trockman; Hrayr Harutyunyan; J. Zico Kolter; Sanjiv Kumar; Srinadh Bhojanapalli (CoRR, 2024)

A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs. - Ankit Singh Rawat; Veeranjaneyulu Sadhanala; Afshin Rostamizadeh; Ayan Chakrabarti; Wittawat Jitkrittum; Vladimir Feinberg; Seungyeon Kim 001; Hrayr Harutyunyan; Nikunj Saunshi; Zachary Nado; Rakesh Shivanna; Sashank J. Reddi; et al. (CoRR, 2024)

Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA. - Sangmin Bae; Adam Fisch; Hrayr Harutyunyan; Ziwei Ji; Seungyeon Kim 001; Tal Schuster (ICLR, 2025)

Continuous Chain of Thought Enables Parallel Exploration and Reasoning. - Halil Alperen Gozeten; Muhammed Emrullah Ildiz; Xuechen Zhang 007; Hrayr Harutyunyan; Ankit Singh Rawat; Samet Oymak (CoRR, 2025)

Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation. - Sangmin Bae; Yujin Kim; Reza Bayat; Sungnyun Kim; Jiyoun Ha; Tal Schuster; Adam Fisch; Hrayr Harutyunyan; Ziwei Ji; Aaron Courville; Se-Young Yun (CoRR, 2025)