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Self-correction

4 open-access journal articles on self-correction, 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

Errors That Should Compound, and When They Do: The Product Rule Assumes Independent Steps, Conformal Guarantees Assume Exchangeable Instances, and the Unit of Independence Decides What Each Can Claim

Two bodies of work quantify uncertainty in multi-step language-model reasoning, and both rest on an independence assumption placed at some unit. Step-level error models multiply per-step reliabilities, which, at an illustrative 95% per-step accuracy, predicts that a fifty-step chain succeeds about…

Cite Related research LOR-00077 · 14 views · 55 downloads
PDF551.4 KB

Journal article

A Lesson Is an Untested Counterfactual: The Three Claims Inside a Stored Agent Failure Memory, Which of Them Anything Checks, and Why Every Published Retention Rule Keys on a Proxy

An agent that fails a task and writes down what it should have done instead has produced a specific kind of object: a sentence asserting that a named step caused the failure and that a named alternative would not have. A stored lesson carries three separable claims - that the trajectory failed…

Cite Related research LOR-00029 · 7 views · 24 downloads
PDF499.2 KB

Journal article

Consistency Is Not Correctness: What Internal Contradiction Detection Certifies, Why the Entailment Is Disjunctive, and Which Decisions It Leaves Unlicensed

Contradiction detection occupies an unusual position among proposals for making a language model check itself. Comparing two of a model's own outputs appears to need no external oracle, which makes it look like the one exception to the observation that working hallucination detectors sit outside…

Cite Related research LOR-00009 · 7 views · 15 downloads
PDF485.9 KB

Journal article

The Self-Verification Gap: Why Working Hallucination Detectors Are External, and What Real-Time Correction Would Actually Require

Large language models generate fluent text that is sometimes false, and a substantial literature now proposes to have the model notice and repair those errors while it writes. Semantic entropy detects confabulations across datasets and tasks without prior knowledge of the task (Farquhar et al…

Cite Related research LOR-00041 · 9 views · 38 downloads
PDF541.9 KB

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