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181 records found · page 5 of 10
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Journal article
Kuwait Gratuity Calculator 2026: A Practical Employee Guide
Learn how to use a Kuwait Gratuity Calculator to estimate end-of-service indemnity. Understand Article 51, salary requirements, service years, resignation rules, and final settlement calculations.
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Journal article
Deskilling Is Not One Endpoint: Five Quantities Behind Assisted Gains and Unassisted Losses in Clinical AI, Why Two Studies of the Same Design Disagree, and Why a Within-Clinician Trial's Control Arm Has Already Been Exposed
Clinical AI tools are approved and bought on one endpoint, the performance of a clinician working with the tool, while a second literature asks what happens to the same clinician working without it. The two are usually set against each other as gain against loss. This paper argues that…
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Journal article
A Control Knob Is Not a Concept: What a Working Steering Vector Licenses, Why Its Equivalence Class Is Set by the Readout That Scores It, and the Controls That Would Upgrade Control to Representation
Adding a vector to a language model's residual stream and watching a behaviour change has become the field's most common argument that the model represents a concept along that vector. Refusal directions, persona vectors, truth directions and instruction vectors are all reported this…
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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…
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Preprint
Théorie du broyeur recycleur et du déséquilibre autogravitatiinnel
L'univers est fini et fermé, un trou noir final broie toute matière comme un broyeur recycleur de métaux, la transforme en énergie pure sous haute pression Pint. Sa gravité G fait le tour de l'univers fini et revient (Gretour ) s'appliquer sur lui même. Gretour +Pint crée une instabilité…
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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
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…
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Journal article
One Pass, Three Purchases: Deduplication's Efficiency, Generalisation and Privacy Arguments Each Hold in Their Own Regime, Rest on Different Properties of the Repetition Distribution, and Cannot All Be Bought With One Similarity Threshold
Deduplication became a fixed stage of language-model pretraining on the strength of three claims made together: removing duplicates saves compute, improves what the model learns, and reduces memorisation and therefore privacy risk. A reading of the literature from 2024 to 2026 can make…
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Journal article
Three Hazards Under One Horizon: Constant-Hazard, Degrading-Step and Log-Logistic Accounts of Agent Failure Describe Different Levels of the Same Data, the 50 Percent Trend Barely Depends on Which Is Right, and Every High-Reliability Forecast Does
Forecasts of autonomous AI capability increasingly rest on one number: the length of task, measured in human working time, that an agent completes half the time. That number has doubled roughly every seven months, and three accounts of why agents fail on longer tasks now sit behind its…
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Preprint
The Shnoudi Holographic Tensor-Network Construction An Explicit Construction with Independent Computational Cross-Checks on Mathieu-Group Combinatorial Geometry, with a Precisely Scoped Verification of Ryu–Takayanagi Entropy and the Entanglement First Law
This note constructs an explicit tensor network from combinatorial data associated with the Mathieu group M11 and the extended binary Golay code, and tests it against two structures from the holographic tensor-network literature: the Ryu–Takayanagi minimal-cut entropy formula and the…
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Journal article
No Stable Self: What Self-Referential Anomaly Defence Can Certify for a Continually Learning System, Why Every Located Guarantee Holds the Benign Distribution Still, and Why Immunology's Own Answer Is a Damage Signal From Outside
Immune-inspired security proposes that a system can protect itself by learning what it normally is and treating departures from that as threats. Continual learning makes departure the normal case: the system is supposed to change, so a poisoning campaign and a legitimate shift in the…
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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…
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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…
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Journal article
A Stated Limit Is a Forecast: What an Agent Can Truthfully Say About Its Own Permissions, Why the Checkable Part Should Never Come From the Model, and How to Score the Part Only the Model Can Supply
Agent interfaces, skill specifications and disclosure proposals increasingly ask a tool-using language-model agent to tell its user what it may and may not do. The self-explanation literature seems to answer whether such statements can be trusted, and its answer seems to be no. This…
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Journal article
The Shnoudi Descent: From the Golay Code and Leech Lattice to Four-Dimensional Triality — 24 to 4 Version Two — A Speculative Mathematical Framework for the Emergence of Four-Dimensional Geometry and Particle Symmetry
This document develops a mathematical construction connecting the Golay code and Leech lattice, in twenty-four dimensions, to a four-dimensional, triality-based particle symmetry structure. Every computational claim is verified by 55 independently runnable Python scripts, provided as a…
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Journal article
Age Is Not Evidence of Staleness: A Recency Decay Is a One-Rate Survival Model, the Rate Belongs to the Fact Rather Than the Clock, and the Silent Change Only a Rate Could Catch Is the Case No Agent-Memory Benchmark Scores
Language agents that keep memories across sessions usually discount a record by how long ago it was written or last read. That discount was introduced to decide what an agent attends to, but it is increasingly read as a statement about whether a record is still true. This paper examines…
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Journal article
Did the Model Change, or Did Your Measurement? A Drift Claim Is a Test Against a Declared Null, the Careful Longitudinal Studies Mostly Caught Announced Version Moves, and a Capability Change Under a Pinned Identifier Is the Claim the Evidence Supports Least
Two bodies of work describe the same deployed language models in opposite terms. One reports that models behind a fixed product name change over time and calls for continuous monitoring. The other reports that a single model, queried twice under settings meant to be deterministic…
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Journal article
Detectors Say 'Different', Not 'What': Score, Deviation and Name Are Three Claims With Three Referees, Only the Name Needs a Referee Outside the Detector, and Published Results Show Novelty Detected Far More Reliably Than It Is Named
An anomaly or novelty detector reports that an input is unlike the data it was built from. Users want more: they want to know what the unusual thing is. Explainable anomaly detection is often presented as supplying that second answer, but three different claims travel under the one word…
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Journal article
The Precursor Assumption: What an Early-Warning Threshold Must Deliver in a Frontier Safety Framework, Why the Continuity Evidence Covers Aggregates Under Fixed Elicitation Rather Than the Thresholded Task, and the Lead Time No Published Record Measures
Frontier safety frameworks decide when a model needs stronger safeguards by testing it against capability thresholds at a fixed cadence, and they place an early-warning threshold below each capability threshold so that mitigations can be prepared in time. That design is sound only if a…
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Journal article
The Evaluator Is the Bottleneck: What a Self-Modifying System's Acceptance Test Must Satisfy Before Its Verdict Can Be Trusted, Why Co-Evolving Evaluators Shrink the External Anchor Rather Than Remove It, and How Moving the Anchor Outside Moves the Attack Surface With It
Self-modifying AI systems now decide which changes to their own code to keep by running an acceptance test and retaining whatever scores higher. Published coding-agent loops report large benchmark gains this way, and their safety case rests on sandboxes, archives of past versions and the…
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Journal article
Spend the Budget on the Known or the Unknown? Open-Set Active Learning Scores Two Opposed Objectives Under One Name, Its Filtering Side's Own Results Do Not Treat Unknowns as Waste, and the Winner Is Set by a Relevance Label and a Query Price the Benchmarks Fix in Advance
Active learning chooses which unlabelled examples a human should label. When the unlabelled pool contains classes the model has never been shown, two lines of work give opposite instructions under the same name. One, usually called open-set active learning or active open-set annotation…