9 citations · 16 across the 15 of their papers we have counts for
4 papers · 1 filter
COMPASS: Finding Where Reasoning Lives in Language Models
Pratyay Dutta, Kowshik Thopalli, Vivek Narayanaswamy
Explicitly eliciting reasoning substantially improves LLM performance. Existing approaches require a predefined characterization of reasoning, whether through CoT prompt design, co…
Unsupervised Latent Space Alignment with Hyperspherical Geodesic Matching
Cameron Ryan, Vivek Sivaraman Narayanaswamy, Kowshik Thopalli +1
Independently trained neural networks tend to encode the same data with similar latent geometries. These latent geometries are not directly compatible, yet they can be nearly the s…
Improving Robustness In Sparse Autoencoders via Masked Regularization
Vivek Narayanaswamy, Kowshik Thopalli, Bhavya Kailkhura +1
Sparse autoencoders (SAEs) are widely used in mechanistic interpretability to project LLM activations onto sparse latent spaces. However, sparsity alone is an imperfect proxy for i…
The Anatomy of Uncertainty in LLMs
Aditya Taparia, Ransalu Senanayake, Kowshik Thopalli +1
Understanding why a large language model (LLM) is uncertain about the response is important for their reliable deployment. Current approaches, which either provide a single uncerta…