Recent Publications
- ELMO: Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces.
Jinbin Zhang, Nasib Ullah, Erik Schultheis, and Rohit Babbar.
42nd International Conference on Machine Learning, ICML 2025, Vancouver, Canada [PDF] [Code]
- UniDEC: Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification.
Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Cho-Jui Hsieh, and Rohit Babbar.
The Web Conference, WebConf 2025, Sydney, Australia [PDF]
- How Well Calibrated are Extreme Multi-label Classifiers? An Empirical Analysis.
Nasib Ullah, Erik Schultheis, Jinbin Zhang and Rohit Babbar.
31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025, Toronto, Canada [PDF] [Code]
- Large Language Model as a Teacher for Zero-shot Tagging at Extreme Scales.
Nasib Ullah, Jinbin Zhang and Rohit Babbar.
31st International Conference on Computational Linguistics, COLING, 2025, Abu-Dhabi, UAE [PDF] [Code]
- Navigating Extremes : Dynamic Sparsity in Large Output Spaces.
Nasib Ullah, Erik Schultheis, Mike Lasby, Yani Ioannou and Rohit Babbar.
38th Conference on Neural Information Processing Systems, NeurIPS, 2024, Vancouver, Canada [PDF] [Code]
- Gandalf : Learning Label-label correlations in Extreme Multi-label Classification via Label Features. Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, and Rohit Babbar
30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2024, Barcelona, Spain [PDF]
- A General Online Algorithm for Optimizing Complex Performance Metrics.
Wojciech Kotlowski, Erik Schultheis, Marek Wydmuch, Rohit Babbar, and Krzysztof Dembczyński
41st International Conference on Machine Learning, ICML 2024, Vienna, Austria [PDF] [Code]
- Consistent Algorithms for Multi-label Classification with Macro@k Metrics.
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Strom Borman, and Krzysztof Dembczyński.
12th International Conference on Learning Representations, ICLR 2024, Vienna, Austria [PDF] [Code]
- Generalized Test Utilities for Long-tail Performance in Extreme Multi-label Classification.
Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, and Krzysztof Dembczyński
37th Conference on Neural Information Processing Systems, NeurIPS, 2023, New Orleans, USA [PDF][Code]
- Towards Memory-Efficient Training for Extremely Large Output Spaces -- Learning with 500k Labels on a Single Commodity GPU.
Erik Schultheis, and Rohit Babbar
ECML-PKDD, 2023, Torino, Italy [PDF][Code]