Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract). - Arjun Ashok; Chaitanya Devaguptapu; Vineeth N. Balasubramanian (AAAI, 2022)

Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer. - Arjun Ashok; K. J. Joseph; Vineeth N. Balasubramanian (ECCV (27), 2022)

Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks. - Yizhong Wang; Swaroop Mishra; Pegah Alipoormolabashi; Yeganeh Kordi; Amirreza Mirzaei; Atharva Naik; Arjun Ashok; Arut Selvan Dhanasekaran; Anjana Arunkumar; David Stap; Eshaan Pathak; Giannis Karamanolakis; et al. (EMNLP, 2022)

Benchmarking Generalization via In-Context Instructions on 1, 600+ Language Tasks. - Yizhong Wang; Swaroop Mishra; Pegah Alipoormolabashi; Yeganeh Kordi; Amirreza Mirzaei; Anjana Arunkumar; Arjun Ashok; Arut Selvan Dhanasekaran; Atharva Naik; David Stap; Eshaan Pathak; Giannis Karamanolakis; et al. (CoRR, 2022)

Learning Modular Structures That Generalize Out-of-Distribution. - Arjun Ashok; Chaitanya Devaguptapu; Vineeth Balasubramanian (CoRR, 2022)

Extremely Simple Activation Shaping for Out-of-Distribution Detection. - Andrija Djurisic; Nebojsa Bozanic; Arjun Ashok; Rosanne Liu (ICLR, 2023)

Lag-Llama: Towards Foundation Models for Time Series Forecasting. - Kashif Rasul; Arjun Ashok; Andrew Robert Williams; Arian Khorasani; George Adamopoulos; Rishika Bhagwatkar; Marin Bilos; Hena Ghonia; Nadhir Vincent Hassen; Anderson Schneider; Sahil Garg; Alexandre Drouin; et al. (CoRR, 2023)

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. - Arjun Ashok; Étienne Marcotte; Valentina Zantedeschi; Nicolas Chapados; Alexandre Drouin (ICLR, 2024)

Context is Key: A Benchmark for Forecasting with Essential Textual Information. - Andrew Robert Williams; Arjun Ashok; Étienne Marcotte; Valentina Zantedeschi; Jithendaraa Subramanian; Roland Riachi; James Requeima; Alexandre Lacoste; Irina Rish; Nicolas Chapados; Alexandre Drouin (CoRR, 2024)

dsld: A Socially Relevant Tool for Teaching Statistics. - Taha Abdullah; Arjun Ashok; Brandon Estrada; Norman Matloff; Aditya Mittal (CoRR, 2024)

Creating a Cooperative AI Policymaking Platform through Open Source Collaboration. - Aiden Lewington; Alekhya Vittalam; Anshumaan Singh; Anuja Uppuluri; Arjun Ashok; Ashrith Mandayam Athmaram; Austin Milt; Benjamin Smith; Charlie Weinberger; Chatanya Sarin; Christoph Bergmeir; Cliff Chang; et al. (CoRR, 2024)

Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting. - Roland Riachi; Kashif Rasul; Arjun Ashok; Prateek Humane; Alexis Roger; Andrew Robert Williams; Yuriy Nevmyvaka; Irina Rish (CoRR, 2025)

Beyond Naïve Prompting: Strategies for Improved Zero-shot Context-aided Forecasting with LLMs. - Arjun Ashok; Andrew Robert Williams; Vincent Zhihao Zheng; Irina Rish; Nicolas Chapados; Étienne Marcotte; Valentina Zantedeschi; Alexandre Drouin (CoRR, 2025)