arXiv (All)
open access
SPIRAL: Learning to Search and Aggregate
Language model reasoning can be substantially improved at test time via scaffolds that scale inference compute across different primitives -- sequential reasoning within a trace, independently sampled parallel traces, and aggregation of multiple reasoning traces into a final response. During post-tr
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
- Trace Grafting: Cross-Model Reasoning in Large Language Model Code Generation#1092500
- Trace Grafting: Cross-Model Reasoning in Large Language Model Code Generation#1092484
- Escaping Redundant Reasoning: Structure-Aware Search for Inference-Time LLMs#820751
- Every Activation Boosted: Scaling General Reasoner to 1 Trillion Open Language Foundation#986796
- Beyond Compression: Diagnosing How Post-Training Changes Mathematical Reasoning#1132267
Record · ID 1155241
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