All proposals

If a language model can rewrite the software it uses to play a game, how can it tell whether an edit was worth keeping? Jens Lehmann and Sahar Vahdati let each model build a program, play five practice games and revise that program twice. They…

Can a research agent tell when its own calculation has led it astray? In FrontierPhysics, physicists turned investigations from their own laboratories and research groups into 56 problems. An agent receives a brief, explores the literature, chooses a method and submits a manuscript alongside results…

Can a compact text encoder learn representations that agree with vision more closely than those of a much larger language model? This preprint investigates that question through a conditional mathematical theorem and experiments comparing Joint-Embedding Predictive Architectures (JEPAs) with next-token prediction. Its central proposal is…

How can a passenger understand why a self-driving car behaves unexpectedly? This study introduces the Concept-Wrapper Network (CW-Net), which connects a learned planner to human-readable concepts and examines whether explanations improve understanding of vehicle behaviour. Its evaluation combines private-track experiments with a real autonomous vehicle,…

This systematic review examines how language-model agents are being used in cybersecurity, from penetration testing and threat intelligence to incident response. It classifies 59 studies published between January 2022 and April 2026 by security function, agent architecture, knowledge augmentation, human oversight and evaluation rigor. The…

Can language models help reviewers find methodological weaknesses in clinical-trial reports? This preprint tests fifteen models on documents containing deliberately inserted errors, first using reports from an earlier human-review experiment and then extending the task to 58 trials published in 2026. It examines detection scores,…

How useful are AI-generated scientific ideas to the researchers who understand the underlying work? This study asks authors of recent preprints to evaluate model-generated hypotheses for novelty, feasibility, plausibility and willingness to adopt them. Its source corpus spans 121,640 preprints, predominantly in biology and medicine,…

Do standard recommendation benchmarks genuinely require sophisticated models, or can their structure reward simpler shortcuts? This study investigates that question with a graph heuristic that starts from a user’s last one or two interactions, retrieves nearby candidate items and ranks them by feature similarity. Across…

In healthcare, a fluent answer can be less useful than a justified decision not to answer. This review examines how language models abstain when information is uncertain or when a response could be harmful. It distinguishes uncertainty-driven abstention from safety-driven refusal and finds that many…

AlphaGenome addresses a central problem in genomics: predicting how changes in DNA affect the regulation of biological activity. The model processes DNA sequences one million bases long and produces thousands of functional predictions, with resolution reaching individual base pairs for supported outputs. Its scope includes…

Malicious software (malware) causes much harm to our devices and life. We are eager to understand the malware behavior and the threat it made. Most of the record files of malware are variable length and text-based files with time stamps, such as event log data…

«AutoQML, self-assembling circuits, hyper-parameterized Quantum ML platform, using cirq, tensorflow and tfq. Trillions of possible qubit registries, gate combinations and moment sequences, ready to be adapted into your ML flow. Here I demonstrate climatechange, jameswebbspacetelescope and microbiology vision applications… [Thus far, a circuit with 16-Qubits and a gate sequence…