Million Tutoring Moves (MTM): An Open Multimodal Dataset for the Science of Tutoring
2026-05-12T07:23:49Z•75275e2a0e083d2eb94642b5f857cd9178b5c1f0e90a71ed8d4d6462754f0e8d
AI-companionAI-safetyLLM-auditMedThinkarXivclinical-reasoningdark-patternsdatasetdeception-detectiondeepfakedigital-twinseducationethicsfrontier-AIjob-searchknowledge-distillationlearning-analyticsmedia-forensicsmedical-AImultimodalreproducibilityteacher-perceptionstrusttutoring
What happened
Collection of newly announced arXiv CS.CY papers (12 May 2026) covering research on tutoring datasets and learning analytics, AI companion apps and dark patterns, distillation techniques for clinical reasoning in small models (MedThink), calls for reproducibility standards for frontier AI safety claims, trustworthiness in digital twin systems, a large cross-national audit of teachers' perceptions of AI and LLM alignment, modeling student effort via response-time propensities, media-forensics reframed toward detecting deception (not just artifact realism), and an ethics-focused study of CS-stud
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- 75275e2a0e083d2eb94642b5f857cd9178b5c1f0e90a71ed8d4d6462754f0e8d
- Enrichment time
- 2026-05-12T07:23:49Z
- AI-assisted enrichment
- Yes
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