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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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10 results for “bias-awareness”

PAC-MCTS: Bias-Aware Pruning for Robust LLM-Guided Search and Planningcs.LG

PAC-MCTS addresses biased search in LLM-guided planning by dynamically pruning.

problem Systematic biases in LLMs lead to inefficient and unsafe search in deep planning tasks.

method Formulates node expansion as BAI under bounded bias, derives sample complexity bounds, and proposes PAC-MCTS for dynamic confidence bounds.

result PAC-MCTS improves robustness and efficiency by up to 78% fewer API evaluations and 3x higher sample efficiency.

bias-aware pruning LLM-guided planning sample complexity information theory dynamic confidence bounds

2026-04-15abs ↗pdf ↗

Kernel Robust Bias-Aware Prediction under Covariate Shiftcs.LG

Under covariate shift, training (source) data and testing (target) data differ in input space distribution, but share the same conditional label distribution. This poses a challenging machine learning task. Robust Bias-Aware (RBA) prediction provides the conditional label distribution that is robust to the worstcase lo…

2017-12-28abs ↗pdf ↗

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-playcs.LG

ISP improves DNN uncertainty for better subgroup accuracy.

problem Improving accuracy-group robustness in deep neural networks.

method Introspective Self-play (ISP) adds an introspection task to improve bias-awareness and uncertainty.

result ISP improves the accuracy-group robustness trade-off of AL methods.

deep learning uncertainty estimation active learning bias-awareness deep neural networks

2023-02-11abs ↗pdf ↗

Bias-Aware Conformal Prediction for Metric-Based Imaging Pipelinesstat.ML

Study improves confidence measures in medical imaging pipelines by addressing bias.

problem Bias in metric-based imaging pipelines compromises the efficiency of prediction intervals.

method Formalized symmetric and asymmetric CP formulations, analyzed bias effects, and validated empirically.

result Symmetric intervals are inflated by bias, while asymmetric intervals remain unaffected.

Bias Conformal Prediction Medical Imaging Confidence Intervals Radiation Therapy Planning

2024-10-07abs ↗pdf ↗

FinReflectKG -- EvalBench: Benchmarking Financial KG with Multi-Dimensional Evaluationq-fin.CP

FinReflectKG - EvalBench benchmarks financial KG extraction from SEC 10-K filings.

problem Lack of universal benchmark and evaluation framework for financial KG construction.

method Agentic and holistic evaluation principles, deterministic commit-then-justify judging protocol, binary and ordinal evaluations.

result Reflection-based extraction outperforms single-pass extraction in comprehensiveness, precision, and relevance.

financial KG SEC 10-K filings LLM extraction evaluation framework bias controls

2025-10-07abs ↗pdf ↗

DISCOVER: Making Vision Networks Interpretable via Competition and Dissectioncs.CV

This work makes vision networks more interpretable by identifying key neurons.

problem Complex deep networks are hard to interpret, hindering safety-critical applications.

method Uses stochastic local competition and multimodal models to dissect and interpret neurons.

result The method generates understandable descriptions for a few active neurons, revealing network decision-making.

interpretability deep learning vision networks neuron dissection stochastic competition

2023-10-07abs ↗pdf ↗

Fighting Sampling Bias: A Framework for Training and Evaluating Credit Scoring Modelsstat.ML

The paper tackles sampling bias in credit scoring models and proposes methods to improve their training and evaluation.

problem Sampling bias in credit scoring models leads to an incomplete representation of the borrower population.

method Bias-aware self-learning framework and Bayesian evaluation method to correct for bias.

result Bayesian evaluation outperforms standard accuracy measures in predicting future performance.

credit scoring sampling bias reject inference Bayesian evaluation profitability

2024-07-17abs ↗pdf ↗

Online Bayesian Calibration under Gradual and Abrupt System Changescs.LG

BRPC online Bayesian calibration handles gradual and abrupt system changes.

problem Aligning model outputs with field observations in evolving systems.

method Bayesian Recursive Projected Calibration (BRPC) for streaming data under simulator mismatch and nonstationarity.

result Improves calibration accuracy under gradual changes and robustness under abrupt regime shifts.

Bayesian calibration online learning system drift data assimilation restart mechanisms

2026-05-07abs ↗pdf ↗

Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inferencestat.ML

New method corrects selection bias in complex models.

problem Selection bias in statistical studies leading to systematic distortions.

method Amortized Bayesian inference with neural posterior estimation.

result Recover well-calibrated posterior distributions across diverse selection mechanisms.

selection bias Bayesian inference simulation-based inference neural posterior estimation posterior calibration

2026-04-20abs ↗pdf ↗

Score-based generative emulation of impact-relevant Earth system model outputsphysics.ao-ph

Generative models emulate climate model outputs for impact assessment.

problem Outdated climate model projections hinder adaptation and mitigation planning.

method Score-based diffusion on a spherical mesh, trained on monthly ESM fields.

result Generative models produce distributions closely matching ESM outputs.

climate modeling impact assessment generative models Earth System Models deep learning

2025-10-05abs ↗pdf ↗