arXiv (All)
open access
Can a Language Model Write the Weights? An Empirical Study of LLM-Written Scoring Networks for Column Generation and MILP Branching, with a Bus-Driver Scheduling Application
This paper was generated by an AI model (Claude Opus 5.5, Anthropic) under the author's direction; all results come from computations run on the author's machine, and every reference was checked. Weight-space programming (WSP) is the idea that a large language model (LLM) can write the weights of a
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
- Post-Hoc Attention Steering of Large Language Models for Robust Code Understanding under Obfuscation#1062005
- Speculative Decoding for Mixture-of-Experts Models: Expert Bytes, Kernel Bandwidth and the Best Draft Length#1457594
- Speculative Decoding for Mixture-of-Experts Models: Expert Bytes, Kernel Bandwidth and the Best Draft Length#1450749
- Only Accepted Tokens Count: An Energy Accounting of Speculative Decoding Under Latency Targets#1491895
- Only Accepted Tokens Count: An Energy Accounting of Speculative Decoding Under Latency Targets#1482957
Record · ID 1625978
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