Large language models (LLMs) are increasingly used to make predictions from numerical time-series histories and textual events. Yet accuracy alone cannot reveal whether correct answers reflect effective integration of the two inputs or instead arise from event polarity, unimodal priors, or superficial cues. Likewise, p...
Jie Gong, Mao-Wei Jiang, Zhiwei Liu et al.· 0 citations
Financial NLP systems produce probabilistic forecasts from news, reports, and filings. Prediction markets can aggregate these forecasts sequentially, but their fees must reward information without overcharging low-risk updates. Existing quadratic-fee mechanisms use a state-blind bound, while a local-curvature envelope...
Yankai Chen, Rassul Magauin, Bowei He et al.· 1 citation
This work instantiates AutoCRAT, a decoder-side controller for frozen backbones that operates over a discrete action space and updates control decisions only at semantic boundaries, improving stability while remaining responsive to the evolving reasoning process.
Han-Jun Luo, Qiu-Shi Liu, Jing-Yang Zhang et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.