arXiv (All)
open access
Agentic Forecasting with Structured Linguistic Beliefs
We propose the Bayesian Linguistic Forecaster (BLF), which is a search-based ReAct style agent for (binary) forecasting that augments its context with a linguistic 'belief state', consisting of a probability estimate and a \emph{structured} natural-language evidence summary. (The belief update is 'B
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
- Agentic Forecasting using Sequential Bayesian Updating of Linguistic Beliefs#120541
- Towards a Physics of Language: Linguistic Physics as a Unified Framework#108824
- LLMs Can Never Be Ideally Rational#112524
- On the Pitfalls of Verbalized Confidence Priors for Calibrating Large Reasoning Models#1116801
- Linguistic practice and false-belief tasks#751759
Record · ID 1118526
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