Ekdeep Singh Lubana
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
8
Active years
2019–2026
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts? | Aaron Mueller, Andrew Lee, Shruti Joshi, Ekdeep Singh Lubana, Dhanya Sridhar, Patrik Reizinger |
| 2026 | ACL | The Impact of Off-Policy Training Data on Probe Generalisation. | Adrians Skapars, Nathalie Maria Kirch, Samuel Dower, Ekdeep Singh Lubana, Dmitrii Krasheninnikov |
| 2025 | ICLR | A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language. | Ekdeep Singh Lubana, Kyogo Kawaguchi, Robert P. Dick, Hidenori Tanaka |
| 2025 | ICLR | ICLR: In-Context Learning of Representations. | Core Francisco Park, Andrew Lee, Ekdeep Singh Lubana, Yongyi Yang, Maya Okawa, Kento Nishi, Martin Wattenberg, Hidenori Tanaka |
| 2025 | ICLR | Competition Dynamics Shape Algorithmic Phases of In-Context Learning. | Core Francisco Park, Ekdeep Singh Lubana, Hidenori Tanaka |
| 2025 | ICLR | Swing-by Dynamics in Concept Learning and Compositional Generalization. | Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana, Maya Okawa, Wei Hu, Hidenori Tanaka |
| 2025 | ICML | Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models. | Thomas Fel, Ekdeep Singh Lubana, Jacob S. Prince, Matthew Kowal, Victor Boutin, Isabel Papadimitriou, Binxu Wang, Martin Wattenberg, Demba E. Ba, Talia Konkle |
| 2025 | ICML | Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing. | Kento Nishi, Rahul Ramesh, Maya Okawa, Mikail Khona, Hidenori Tanaka, Ekdeep Singh Lubana |
| 2025 | NAACL | Analyzing (In)Abilities of SAEs via Formal Languages. | Abhinav Menon, Manish Shrivastava, David Krueger, Ekdeep Singh Lubana |
| 2024 | ICLR | In-Context Learning Dynamics with Random Binary Sequences. | Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman |
| 2024 | ICLR | Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. | Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktschel, Edward Grefenstette, David Scott Krueger |
| 2024 | ICML | Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. | Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka |
| 2024 | ICML | Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks. | Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona, Robert P. Dick, Hidenori Tanaka |
| 2023 | ICLR | What shapes the loss landscape of self supervised learning? | Liu Ziyin, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka |
| 2023 | ICML | Mechanistic Mode Connectivity. | Ekdeep Singh Lubana, Eric J. Bigelow, Robert P. Dick, David Scott Krueger, Hidenori Tanaka |
| 2022 | ICML | Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering. | Ekdeep Singh Lubana, Chi Ian Tang, Fahim Kawsar, Robert P. Dick, Akhil Mathur |
| 2022 | WWW | Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. | Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra |
| 2021 | ICLR | A Gradient Flow Framework For Analyzing Network Pruning. | Ekdeep Singh Lubana, Robert P. Dick |
| 2020 | CVPR | Intelligent Scene Caching to Improve Accuracy for Energy-Constrained Embedded Vision. | Benjamin Simpson, Ekdeep Singh Lubana, Yuchen Liu, Robert P. Dick |
| 2019 | DCC | Machine Foveation: An Application-Aware Compressive Sensing Framework. | Ekdeep Singh Lubana, Vinayak Aggarwal, Robert P. Dick |
| 2019 | ICIP | Minimalistic Image Signal Processing for Deep Learning Applications. | Ekdeep Singh Lubana, Robert P. Dick, Vinayak Aggarwal, Pyari Mohan Pradhan |