Arjun Ashok

According to our database, Arjun Ashok authored at least 17 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Overcoming the Modality Gap in Context-Aided Forecasting.

Vincent Zhihao Zheng, Étienne Marcotte, Arjun Ashok, Andrew Robert Williams, Lijun Sun, Alexandre Drouin, Valentina Zantedeschi

CoRR, March, 2026

Impermanent: A Live Benchmark for Temporal Generalization in Time Series Forecasting.

Azul Garza, Reneé Rosillo, Rodrigo Mendoza-Smith, David Salinas, Andrew Robert Williams, Arjun Ashok, Mononito Goswami, José Martín Juárez

CoRR, March, 2026

Multi-Ecosystem Modeling of OSS Project Sustainability.

Arjun Ashok, Nafiz Imtiaz Khan, Swati Singhvi, Stefan Stanciulescu, Zhouhao Wang, Vladimir Filkov

CoRR, February, 2026

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, August, 2025

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, June, 2025

OSSPREY: AI-Driven Forecasting and Intervention for OSS Project Sustainability.

Nafiz Imtiaz Khan, Priyal Soni, Arjun Ashok, Vladimir Filkov

Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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, Daivik Patel, Daniel Li, David Bell, Defu Cao, Donghwa Shin, Edward Kang, Edwin Zhang, Enhui Li, Felix Chen, Gabe Smithline, Haipeng Chen, Henry Gasztowtt, Hoon Shin, Jiayun Zhang, Joshua Gray, Khai Hern Low, Kishan Patel, Lauren Hannah Cooke, Marco Burstein, Maya Kalapatapu, Mitali Mittal, Raymond Chen, Rosie Zhao, Sameen Majid, Samya Potlapalli, Shang Wang, Shrenik Patel, Shuheng Li, Siva Komaragiri, Song Lu, Sorawit Siangjaeo, Sunghoo Jung, Tianyu Zhang, Valery Mao, Vikram Krishnakumar, Vincent Zhu, Wesley Kam, Xingzhe Li, Yumeng Liu

CoRR, 2024

dsld: A Socially Relevant Tool for Teaching Statistics.

Taha Abdullah, Arjun Ashok, Brandon Estrada, Norman Matloff, Aditya Mittal

CoRR, 2024

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series.

Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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, Nicolas Chapados, Yuriy Nevmyvaka, Irina Rish

CoRR, 2023

Extremely Simple Activation Shaping for Out-of-Distribution Detection.

Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, Rosanne Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning Modular Structures That Generalize Out-of-Distribution.

Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian

CoRR, 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, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy A, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi, Noah A. Smith, Daniel Khashabi

CoRR, 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, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Kuntal Kumar Pal, Maitreya Patel, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Savan Doshi, Shailaja Keyur Sampat, Siddhartha Mishra, Sujan Reddy A, Sumanta Patro, Tanay Dixit, Xudong Shen

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer.

Arjun Ashok, K. J. Joseph, Vineeth N. Balasubramanian

Proceedings of the Computer Vision - ECCV 2022, 2022

Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract).

Arjun Ashok, Chaitanya Devaguptapu, Vineeth N. Balasubramanian

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022