Practical Near Neighbor Search via Group Testing. - Joshua Engels; Benjamin Coleman; Anshumali Shrivastava (NeurIPS, 2021)

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; et al. (CIKM, 2023)

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries. - Joshua Engels; Benjamin Coleman; Vihan Lakshman; Anshumali Shrivastava (NeurIPS, 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 (RecSys, 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)

PECANN: Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search. - Shangdi Yu; Joshua Engels; Yihao Huang 004; Julian Shun (CoRR, 2023)

Approximate Nearest Neighbor Search with Window Filters. - Joshua Engels; Benjamin Landrum; Shangdi Yu; Laxman Dhulipala; Julian Shun (ICML, 2024)

Not All Language Model Features Are Linear. - Joshua Engels; Isaac Liao; Eric J. Michaud; Wes Gurnee; Max Tegmark (CoRR, 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 One-Dimensionally Linear. - Joshua Engels; Eric J. Michaud; Isaac Liao; Wes Gurnee; Max Tegmark (ICLR, 2025)

Efficient Dictionary Learning with Switch Sparse Autoencoders. - Anish Mudide; Joshua Engels; Eric J. Michaud; Max Tegmark; Christian Schröder de Witt (ICLR, 2025)

Decomposing The Dark Matter of Sparse Autoencoders. - Joshua Engels; Logan Riggs Smith; Max Tegmark (Trans. Mach. Learn. Res., 2025)

Low-Rank Adapting Models for Sparse Autoencoders. - Matthew Chen; Joshua Engels; Max Tegmark (CoRR, 2025)

Are Sparse Autoencoders Useful? A Case Study in Sparse Probing. - Subhash Kantamneni; Joshua Engels; Senthooran Rajamanoharan; Max Tegmark; Neel Nanda (CoRR, 2025)

Scaling Laws For Scalable Oversight. - Joshua Engels; David D. Baek; Subhash Kantamneni; Max Tegmark (CoRR, 2025)

Dense SAE Latents Are Features, Not Bugs. - Xiaoqing Sun; Alessandro Stolfo; Joshua Engels; Ben Wu 001; Senthooran Rajamanoharan; Mrinmaya Sachan; Max Tegmark (CoRR, 2025)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)

Simple Mechanistic Explanations for Out-Of-Context Reasoning. - Atticus Wang; Joshua Engels; Oliver Clive-Griffin; Senthooran Rajamanoharan; Neel Nanda (CoRR, 2025)

CleANN: Efficient Full Dynamism in Graph-based Approximate Nearest Neighbor Search. - Ziyu Zhang; Yuanhao Wei; Joshua Engels; Julian Shun (CoRR, 2025)