5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan +2
Sparse autoencoders (SAEs) are a popular method for interpreting concepts represented in large language model (LLM) activations. However, there is a lack of evidence regarding the…
cs.AI2025★ 5 cited
Language Models Use Trigonometry to Do Addition
Subhash Kantamneni, Max Tegmark
Mathematical reasoning is an increasingly important indicator of large language model (LLM) capabilities, yet we lack understanding of how LLMs process even simple mathematical tas…
cs.LG2024★ 1 cited
OptPDE: Discovering Novel Integrable Systems via AI-Human Collaboration
Subhash Kantamneni, Ziming Liu, Max Tegmark
Integrable partial differential equation (PDE) systems are of great interest in natural science, but are exceedingly rare and difficult to discover. To solve this, we introduce Opt…