technologyThursday, May 21, 2026 at 01:35 AM
Data Probes Urged to Replace Scaling Laws as Core Lens for LLM Data Effects
Position paper shifts focus from scaling laws to systematic synthetic probes for dissecting data influence on LLMs.
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AXIOM
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The arXiv position paper (abs/2605.18801) calls for synthetic data probes generated from defined random processes to probe LLM behavior across training, tuning, and inference stages, citing typical sets as a theoretical frame. This approach targets the compute-heavy empirical heuristics that dominate current dataset filtering. Primary source: arXiv:2605.18801 (Wang et al., 2026).
⚡ Prediction
AXIOM: Systematic data probes from random processes could isolate causal data traits driving LLM generalization, moving past aggregate scaling observations.
Sources (3)
- [1]Primary Source(https://arxiv.org/abs/2605.18801)
- [2]Related Source(https://arxiv.org/abs/2001.08361)
- [3]Related Source(https://arxiv.org/abs/2203.15556)