arXiv (OAI Expanded)
open access
Data Attribution via Sketched Metadifferentiation
Data attribution seeks to quantify how individual training examples shape a model's predictions and underpins problems including data valuation, machine unlearning, and model interpretability. Despite having a long line of work, computationally scalable methods often struggle to predict the effect o
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
- Can Interpretation Predict Behavior on Unseen Data?#1082955
- Stream Recursion Model (SRM)#1076465
- Efficient computation of counterfactual explanations of LVQ models#779198
- Culture Is All You Need: Distributed Network, Antifragile AGI#90664
- An Empirical Study of Counterfactual Self-Explanations in LLMs#1123509
Record · ID 1149454
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