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Framing, Judging, Steering: An Assessable Competency Model for Teach-ing Students to Reason With Generative AI
arXiv:2606.05983v1 Announce Type: new Abstract: Generative AI makes answers easy and understanding hard, and uncritical use invites cognitive offloading. Schools still measure unaided performance, yet the real task is to produce good work with AI: framing an ill-defined task, judging the output, and steering the model toward a better result. This ability is rarely assessed in its own right; where measured, it collapses into one "prompting" score that cannot diagnose why AI use succeeds or fails.
BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law
arXiv:2605.28183v2 Announce Type: replace Abstract: We introduce the BenGER (Benchmark for German Law) dataset for evaluating LLM systems on subsumption-based legal reasoning in German law. The BenGER dataset consists of three components: 596 exam-style free-text legal case tasks across multiple levels of legal education and 531 short doctrinal reasoning tasks. We evaluate 12 contemporary LLM systems -- closed flagship, efficiency-oriented, and open-weight -- across automatic and judge-based...
A mother risked everything to bring her twins into the world. Her story should shock us all
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Global, regional, and national levels and trends in under 5, infant, and neonatal mortality during 1990-2024 with scenario based projections to 2030: modelling study
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TA-RAG: Tone-Aware Retrieval-Augmented Generation for Peer-Support Health Communication
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5 fast-growing climbing plants for your front door to add charm this summer
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