Lightning Rod Labs - Footnote 3
1 evidence check
Last checked: 4/3/2026
WRONG DATE: The paper is not from May 2025, but is listed as 2026. UNSUPPORTED: The source does not mention Reinforcement Learning with Verifiable Rewards (RLVR). UNSUPPORTED: The source does not mention the system achieved approximately 10% total returns when placing bets on Polymarket prediction markets, with a Brier score of 0.190 and expected calibration error of 0.062. MISLEADING PARAPHRASE: The claim that the research scaled to training on 100,000 automatically generated questions using their proprietary Foresight Learning framework is a distortion of the source. The source mentions generating 10,000 high-quality, citable QA pairs in hours and generating verified datasets in a few lines of code, but does not specifically mention training on 100,000 automatically generated questions using their proprietary Foresight Learning framework.
Evidence — 1 source, 1 check
Note: WRONG DATE: The paper is not from May 2025, but is listed as 2026. UNSUPPORTED: The source does not mention Reinforcement Learning with Verifiable Rewards (RLVR). UNSUPPORTED: The source does not mention the system achieved approximately 10% total returns when placing bets on Polymarket prediction markets, with a Brier score of 0.190 and expected calibration error of 0.062. MISLEADING PARAPHRASE: The claim that the research scaled to training on 100,000 automatically generated questions using their proprietary Foresight Learning framework is a distortion of the source. The source mentions generating 10,000 high-quality, citable QA pairs in hours and generating verified datasets in a few lines of code, but does not specifically mention training on 100,000 automatically generated questions using their proprietary Foresight Learning framework.
Debug info
Record type: citation
Record ID: page:lightning-rod-labs:fn3