arXiv (OAI Expanded)
open access
SABER-Math: Automated Benchmark for Information Retrieval Evaluation in Mathematics
As agentic AI systems tackle more complex mathematical tasks, they increasingly rely on information retrieval (IR) to search problem databases, theorem libraries, and educational resources. However, choosing the right retriever remains difficult, as it is infeasible to directly isolate its effect on
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
- SABER-Math: Automated Benchmark for Information Retrieval Evaluation in Mathematics#924103
- EvalLoop: A Methodology for Evaluation-Driven Iterative Improvement of Business AI Systems#346594
- Algebraic Retrieval: Composable Search for Agents#1014076
- Enhancing Clinical Trial Patient Matching through Knowledge Augmentation and Reasoning with Multi-Agent#128322
- A Clinical AI-Based System (MoodMon) for Affective Disorders: Algorithm Development and Validation.#645506
Record · ID 919874
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