arXiv (All)
open access
Improving Test-Time Scaling with Adaptive Looped Transformers
Looped transformers have demonstrated promising parameter efficiency by reusing layers for latent computation. Prior studies compare looped and non-looped models at matched parameters or per-token FLOPs. However, to the best of our knowledge, whether looping improves test-time scaling as outputs gro
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
- Improving Test-Time Scaling with Adaptive Looped Transformers#1108746
- Scheduling Recursive Reasoning in Looped Transformers#1131854
- A Review of Accelerated Test Models#168049
- OR-Transformer: Scaling Real-Time Decision-Making to 1,000 Items#927477
- Compiler-supported reduced precision and AoS-SoA transformations for heterogeneous hardware#984098
Record · ID 1130395
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