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SYNTH is the first open-source synthetic corpus derived from 58,698 Wikipedia articles that collapses pre, mid, and post-training into a single training stage via structured amplification of curated encyclopedic seeds, and opens up possibilities for both generalist models with significantly increased data efficiency, a...
These findings show that aggregate detection metrics conceal persistent, model dependent heterogeneity in language model failures and motivate regime conditioned evaluation.
It is concluded that only by grounding oversight in realistic assumptions about human cognition and institutional incentives can it fulfill its intended role in ensuring trustworthy AI.
BenCheck is proposed, a package for benchmark validity analysis that encapsulates the main checks performed in a case study on HellaSwag and can be used to audit commonsense reasoning benchmarks, including PIQA, Global PIQA, and Winogrande.
Large language models (LLMs) are increasingly deployed for translation tasks, yet their implicit political positioning in such contexts remains understudied. We ask whether a single politically charged framing term, such as aggressor, enemy, neighbour, or coloniser is sufficient to trigger implicit political alignment...
LeakageBench provides a diagnostic benchmark for high-recall, spatially grounded PII redaction in document images and shows that stronger detection and tool assistance improve localization without making most pages safe for release.
This work examines how LLMs respond to user prompts expressing varying degrees of Dark Triad traits (Machiavellianism, Narcissism, and Psychopathy) using a curated dataset, revealing systematic differences across models.
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