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Quantization enables deployment of large language models on resource-constrained clinical edge devices, but its effect on clinical accuracy and safety remains understudied. We evaluate five 7-8B parameter models at FP16, GPTQ-INT8, and GPTQ-INT4 precision across five benchmarks: MedQA, MedMCQA, Med-HALT, a risk-stratif...
The Cognitive Synergy Framework is introduced, a methodology for generating highquality humor data inspired by psychological theories of humor, and model variants significantly outperform larger instruction-tuned baselines and achieve top-tier open-weight performance while remaining competitive with frontier proprietar...
This work introduces the first information retrieval benchmark resource for Ehugbo, a high-quality parallel multimodal corpus constructed from a high-quality parallel multimodal corpus that reveals the ''Alignment Gap'', where African-centric foundation models that excel at linguistic familiarity with Igbo achieve <5%...
A large LLM-capability gap between the two languages is confirmed, and data augmentation experiments across three encoder models show that LLM-generated text consistently hurts downstream NER tasks while producing mixed effects on POS tagging, motivating careful language-specific IR evaluation.
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