Joshua Engels

According to our database, Joshua Engels authored at least 19 papers between 2021 and 2025.

Collaborative distances:

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

2025

CleANN: Efficient Full Dynamism in Graph-based Approximate Nearest Neighbor Search.

Ziyu Zhang, Yuanhao Wei, Joshua Engels, Julian Shun

CoRR, July, 2025

Simple Mechanistic Explanations for Out-Of-Context Reasoning.

Atticus Wang, Joshua Engels, Oliver Clive-Griffin, Senthooran Rajamanoharan, Neel Nanda

CoRR, July, 2025

The Singapore Consensus on Global AI Safety Research Priorities.

Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vanessa Wilfred, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnès Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Johannes Heidecke, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan S. Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán Ó hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sanchez-Pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, William-Chandra Tjhi, Robert Trager, Brian Tse, Anthony Tung K. H., John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Zikelic

CoRR, June, 2025

Dense SAE Latents Are Features, Not Bugs.

Xiaoqing Sun, Alessandro Stolfo, Joshua Engels, Ben Wu, Senthooran Rajamanoharan, Mrinmaya Sachan, Max Tegmark

CoRR, June, 2025

Scaling Laws For Scalable Oversight.

Joshua Engels, David D. Baek, Subhash Kantamneni, Max Tegmark

CoRR, April, 2025

Are Sparse Autoencoders Useful? A Case Study in Sparse Probing.

Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan, Max Tegmark, Neel Nanda

CoRR, February, 2025

Low-Rank Adapting Models for Sparse Autoencoders.

Matthew Chen, Joshua Engels, Max Tegmark

CoRR, January, 2025

Decomposing The Dark Matter of Sparse Autoencoders.

Joshua Engels, Logan Riggs Smith, Max Tegmark

Trans. Mach. Learn. Res., 2025

Efficient Dictionary Learning with Switch Sparse Autoencoders.

Anish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schröder de Witt

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Not All Language Model Features Are One-Dimensionally Linear.

Joshua Engels, Eric J. Michaud, Isaac Liao, Wes Gurnee, Max Tegmark

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

The Geometry of Concepts: Sparse Autoencoder Feature Structure.

Yuxiao Li, Eric J. Michaud, David D. Baek, Joshua Engels, Xiaoqing Sun, Max Tegmark

CoRR, 2024

Not All Language Model Features Are Linear.

Joshua Engels, Isaac Liao, Eric J. Michaud, Wes Gurnee, Max Tegmark

CoRR, 2024

Approximate Nearest Neighbor Search with Window Filters.

Joshua Engels, Benjamin Landrum, Shangdi Yu, Laxman Dhulipala, Julian Shun

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

PECANN: Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search.

Shangdi Yu, Joshua Engels, Yihao Huang, Julian Shun

CoRR, 2023

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Neural Networks on Commodity CPU Hardware.

Nicholas Meisburger, Vihan Lakshman, Benito Geordie, Joshua Engels, David Torres Ramos, Pratik Pranav, Benjamin Coleman, Benjamin Meisburger, Shubh Gupta, Yashwanth Adunukota, Tharun Medini, Anshumali Shrivastava

CoRR, 2023

From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware.

Anshumali Shrivastava, Vihan Lakshman, Tharun Medini, Nicholas Meisburger, Joshua Engels, David Torres Ramos, Benito Geordie, Pratik Pranav, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries.

Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware.

Nicholas Meisburger, Vihan Lakshman, Benito Geordie, Joshua Engels, David Torres Ramos, Pratik Pranav, Benjamin Coleman, Benjamin Meisburger, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain, Tharun Medini, Anshumali Shrivastava

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2021

Practical Near Neighbor Search via Group Testing.

Joshua Engels, Benjamin Coleman, Anshumali Shrivastava

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021