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Evaluation validity

4 open-access journal articles on evaluation validity, published in 2026 in Life of Research. Every record is free to read and download, with a permanent link and a ready-made citation.

4 records

Journal article

Circuits Are Estimates, Not Mechanisms: A Recovered Subgraph Is One Draw From a Class Set by the Ablation, the Dataset and the Grain, the Results That Defend Circuits Hold at the Level of That Class, and What Ablation Evidence Licenses at Each Level

A circuit in a language model is usually presented as the mechanism by which the model performs a task: a sparse subgraph, found by ablation or patching, that reproduces the behaviour when everything else is knocked out. A second body of work, mostly from 2024 to 2026, reports that the subgraph…

Cite Related research LOR-00098 · 7 views · 7 downloads
PDF395.2 KB

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

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 superposition. This paper asks what a latent is evidence…

Cite Related research LOR-00096 · 7 views · 4 downloads
PDF405.3 KB

Journal article

A Contamination Flag Is Not an Inflation Estimate: What Benchmark Contamination Detectors Certify, What Decontamination Is Meant to Buy, and Why the Clean-Subset Comparison That Joins Them Is Biased From Both Sides

Almost every large language model report now includes a contamination analysis: benchmark items that overlap the training corpus are flagged, the model is rescored on the unflagged remainder, and a small gap is read as evidence that the headline numbers stand. Two research literatures sit behind…

Cite Related research LOR-00091 · 8 views · 6 downloads
PDF389.5 KB

Journal article

Agreement Is Not a Criterion: What Matching Human Labels Certifies About an LLM Judge, Why a Shared Shortcut Passes the Test, and Why Every External Criterion Found So Far Validates a Use Rather Than a Judge

An automatic judge is usually accepted on one piece of evidence: it agrees with human preference labels about as often as humans agree with each other. That number is then read as permission to use the judge for ranking models, filtering data, selecting samples and supplying reward. This paper…

Cite Related research LOR-00090 · 15 views · 26 downloads
PDF376.2 KB

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