Cross-Dataset Bloom Question Classification: Supervised Models and Prompted LLMs
2026-06-15T07:23:51Z•603d1df24eeb2530105ffb92b7268a7a75afbe2134a0497e8f9a140f188d838b
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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