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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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0111 · Jul 201919922001200920172026
7 results for FST

FST.ai 2.0 improves Taekwondo decision-making with AI, reducing review time and increasing trust.

problem Fair, transparent, and explainable decision-making in Taekwondo.
method Pose-based action recognition, epistemic uncertainty modeling, interactive dashboards.
result 85% reduction in decision review time, 93% referee trust in AI-assisted decisions.

Paper assesses GMMB in VAs using FST for accurate net liability calculations.

problem Risk management of GMMB under stochastic mortality and regime-switching.
method Net liability model with FST algorithm for accurate numeric solutions.
result FST algorithm provides reliable results for net liability of GMMB.

Enhances interpretability of functional survival models.

problem Lack of interpretability in functional survival models limits practical use.
method Introduces novel methods to enhance interpretability of FST and explainability of FRSF.
result Proposed methods yield efficient, easy-to-understand decision trees.

This paper formalizes Uniswap v3 using PTA and FST for rigorous analysis.

problem Formal modeling of Uniswap v3's concentrated liquidity for rigorous analysis.
method Formal state machine models using PTA and FST, proving rounding bounds.
result Formal justification of Uniswap v3's εε-slack and rounding safety.

A keyword spotting (KWS) system determines the existence of, usually predefined, keyword in a continuous speech stream. This paper presents a query-by-example on-device KWS system which is user-specific. The proposed system consists of two main steps: query enrollment and testing. In query enrollment step, phonetic pos…

2019-10-11abs ↗pdf ↗

Recognizing written domain numeric utterances (e.g. I need $1.25.) can be challenging for ASR systems, particularly when numeric sequences are not seen during training. This out-of-vocabulary (OOV) issue is addressed in conventional ASR systems by training part of the model on spoken domain utterances (e.g. I need one …

2019-07-01abs ↗pdf ↗