Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data

An arXiv paper proposes infinite-parameter LLMs that generate and adapt model weights from live data streams rather than fixed trained parameters.

The arXiv paper 2609.18842, titled 'Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data,' proposes treating LLM weights as functionally infinite parameters generated and adapted from live input data. The paper gained traction on Hacker News with 43 points and 10 comments. Detailed results and benchmarks are not available from the provided metadata.

• Proposes generating and adapting LLM weights dynamically from live data
• Discussed on Hacker News with 43 points and 10 comments