arXiv (All)
open access
Tracing Morphology, Semantics, and Divergence in Language Acquisition
Understanding the dynamics of language acquisition in Large Language Models (LLMs) is crucial for uncovering how statistical representations evolve into structured linguistic capabilities. However, most existing studies focus primarily on fully trained models, leaving the developmental trajectory ac
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Beyond Accuracy: Cross-Linguistic Equity and Socio-Technical Dimensions of Large Language Models#19968
- Why Pretraining Fails to Share Cross-Lingual Knowledge#1013889
- Conformalized Large Language Models under Configuration Shift#793820
- Conformalized Large Language Models under Configuration Shift#789815
- LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations#1014540
Record · ID 1344864
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive