Cross-Dataset Bloom Question Classification: Supervised Models and Prompted LLMs

2026-06-15T07:23:51Z603d1df24eeb2530105ffb92b7268a7a75afbe2134a0497e8f9a140f188d838b
AI-safetyESGEdTechNLPalignmentbiasdataset-generalizationeducationevaluationexistential-riskfairnessgovernancehuman-subjectslarge-language-modelsmachine-learningpromptingtoolingtransit-planning

What happened

Collection of recent AI/ML papers (arXiv) covering: cross-dataset evaluation of Bloom’s taxonomy question classification and LLM prompting (LLMs generalize better than supervised models); PictoPercept — an open-source visual toolkit to measure human and model bias (GPT-5 shows stronger biases than humans); an EduNLP systematic review highlighting misaligned EdTech incentives and under-served teachers; empirical work on ESG narrative scoring showing limited incremental value from reasoning-heavy LLMs relative to cheaper ensembles; position and theory pieces advocating planet-centered AI and re‑

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_cy
Record identifier
603d1df24eeb2530105ffb92b7268a7a75afbe2134a0497e8f9a140f188d838b
Enrichment time
2026-06-15T07:23:51Z
AI-assisted enrichment
Yes

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