Publication2025
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval-Augmented Generation Across Learning Styles
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- International — held abroad
- Journal
- Emnlp 2025 2025 Conference on Empirical Methods in Natural Language Processing Proceedings of the Conference
- Pages
- 13348-13389
- Published
- 1 January 2025
- DOI
- 10.18653/v1/2025.emnlp-main.675
- Scopus ID
- 105040265396
- Authors
- 7
- Open access
- Yes
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- IN, US
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
4 Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
LLM-based pedagogical agents with genetic algorithm adaptation optimize teaching strategies for diverse learners
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-1.1 Education and lifelong learning
AI-assisted adaptive learning systems advance lifelong learning and personalized education
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval-Augmented Generation Across Learning Styles”. Kortex.
