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Preprint

Written Is Not Kept: What a Single-Layer Readout of the Residual Stream Licenses When Adjacent Layers Undo Part of Each Other's Writes, Why Cancellation and Iterative Refinement Are Not Rival Findings, and the Persistence Check Interpretability Claims Skip

Pranay Mahendrakar 2026

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Life of Research Most feature-based interpretability reads a transformer one layer at a time. A probe, a lens or a sparse dictionary is fitted to the residual stream, or to one layer's output, at a chosen depth, and what it finds there is…

Cite Related research LOR-00173 · 2 views · 1 download Select “Written Is Not Kept: What a Single-Layer Readout of the…” for export

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Preprint

A Best Match Is Not a Twin: What Feature Similarity Between State Space Models and Transformers Certifies, Why the Null and the Shared Inputs Decide the Verdict, and the Controls That Would Show Two Architectures Learned the Same Thing

Pranay Mahendrakar 2026

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Life of Research Selective state space models such as Mamba compress the past into a fixed-size state, while Transformers attend over the whole context, and a growing set of studies asks whether the two learn the same internal features. A 2026…

Cite Related research LOR-00142 · 13 views · 13 downloads Select “A Best Match Is Not a Twin: What Feature Similarity…” for export

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Journal article

Dictionaries Without Ontologies: What a Sparse Autoencoder Latent Is Evidence For, Why Decodability, Use and Reproducibility Do Not Add Up to Canonicity, and the Identifiability Premise No Real-Model Result Has Checked

Pranay Mahendrakar 2026

(c) 2026 Pranay Mahendrakar. Licensed under CC BY 4.0. Sparse autoencoders are now the default instrument for decomposing language model activations, and their latents are routinely reported as the model's features: units the network itself uses, which a wide enough dictionary has pulled out of…

Cite Related research LOR-00096 · 35 views · 23 downloads Select “Dictionaries Without Ontologies: What a Sparse Autoencoder…” for export

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