arXiv (All)
open access
LLM Bidders Preserve the Mechanism-Level Orderings of Human Bidders
Training on vast amounts of human-generated data has motivated growing interest in using large language models (LLMs) to simulate human behavior. We ask which features of human behavior general-purpose models preserve when used out of the box in auctions, where multiple bidders interact under explic
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
- Conduct Under Pressure: What Sixty Language Models Do When a User Pushes#1061087
- JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces#1155372
- Lost with a Map: Conversational State and Behavioral Reliability in Language Models#1118956
- One Word, Different Action: A Real-Robot Benchmark for Language-Conditioned Embodied Reasoning#1084374
- Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States#1109998
Record · ID 1128509
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