:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ferreira, Juliett Suárez, Slavkovik, Marija, Casillas, Jorge
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2505.17525
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uncovering Fairness through Data Complexity as an Early Indicator
by: Ferreira, Juliett Suárez, et al.
Published: (2025)

Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness
by: Ferreira, Juliett Suárez, et al.
Published: (2025)

Reinforcement Learning and Machine ethics:a systematic review
by: Vishwanath, Ajay, et al.
Published: (2024)

Argumentative Debates for Transparent Bias Detection [Technical Report]
by: Ayoobi, Hamed, et al.
Published: (2025)

TrueGradeAI: Retrieval-Augmented and Bias-Resistant AI for Transparent and Explainable Digital Assessments
by: Thakur, Rakesh, et al.
Published: (2025)

Whither Bias Goes, I Will Go: An Integrative, Systematic Review of Algorithmic Bias Mitigation
by: Hickman, Louis, et al.
Published: (2024)

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes
by: Block, Adam, et al.
Published: (2025)

Rethinking Refinement: Correcting Generative Bias without Noise Injection
by: Peng, Xin, et al.
Published: (2026)

Correcting Performance Estimation Bias in Imbalanced Classification with Minority Subconcepts
by: Maxson, Taylor, et al.
Published: (2026)

Preference Models assume Proportional Hazards of Utilities
by: Nagpal, Chirag
Published: (2025)

Optimistic Rates for Learning from Label Proportions
by: Li, Gene, et al.
Published: (2024)

Towards Transparent and Efficient Anomaly Detection in Industrial Processes through ExIFFI
by: Frizzo, Davide, et al.
Published: (2024)

CoRPO: Adding a Correctness Bias to GRPO Improves Generalization
by: Garg, Anisha, et al.
Published: (2025)

Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
by: Lv, Jiaqi, et al.
Published: (2026)

Class-Proportional Coreset Selection for Difficulty-Separable Data
by: Tsai, Elisa, et al.
Published: (2025)

Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts
by: Beddows, Matthew, et al.
Published: (2026)

CORTEX: A Cost-Sensitive Rule and Tree Extraction Method
by: Kopanja, Marija, et al.
Published: (2025)

Vanishing Bias Heuristic-guided Reinforcement Learning Algorithm
by: Li, Qinru, et al.
Published: (2023)

Neural Algorithmic Reasoning with Multiple Correct Solutions
by: Kujawa, Zeno, et al.
Published: (2024)

To Predict or Not To Predict? Proportionally Masked Autoencoders for Tabular Data Imputation
by: Kim, Jungkyu, et al.
Published: (2024)

Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement
by: Boche, Holger, et al.
Published: (2024)

EvoFormer: Learning Dynamic Graph-Level Representations with Structural and Temporal Bias Correction
by: Zhong, Haodi, et al.
Published: (2025)

Beyond RLHF and NLHF: Population-Proportional Alignment under an Axiomatic Framework
by: Kim, Kihyun, et al.
Published: (2025)

Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
by: Hirose, Yushi, et al.
Published: (2026)

Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration
by: Papanikou, Vasiliki, et al.
Published: (2025)

Enhancing AI-Based Tropical Cyclone Track and Intensity Forecasting via Systematic Bias Correction
by: Niu, Peisong, et al.
Published: (2026)

Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods
by: Dhaini, Mahdi, et al.
Published: (2025)

Anomaly Correction of Business Processes Using Transformer Autoencoder
by: Gong, Ziyou, et al.
Published: (2024)

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
by: Havaldar, Shreyas, et al.
Published: (2023)

Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration
by: Qi, Shi-ang, et al.
Published: (2024)

The Forecast After the Forecast: A Post-Processing Shift in Time Series
by: Liang, Daojun, et al.
Published: (2026)

Sharper Error Bounds in Late Fusion Multi-view Clustering Using Eigenvalue Proportion
by: Du, Liang, et al.
Published: (2024)

A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
by: Charusaie, Mohammad-Amin, et al.
Published: (2024)

RaanA: A Fast, Flexible, and Data-Efficient Post-Training Quantization Algorithm
by: Yang, Yongyi, et al.
Published: (2025)

Forming Auxiliary High-confident Instance-level Loss to Promote Learning from Label Proportions
by: Ma, Tianhao, et al.
Published: (2024)

Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
by: Ye, Chenlu, et al.
Published: (2025)

HeadQ: Model-Visible Distortion and Score-Space Correction for KV-Cache Quantization
by: Williams, Jorge L. Ruiz
Published: (2026)

KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
by: Xu, Zukang, et al.
Published: (2026)

HURRI-GAN: A Novel Approach for Hurricane Bias-Correction Beyond Gauge Stations using Generative Adversarial Networks
by: Nadera, Noujoud, et al.
Published: (2026)

Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
by: Zhang, Shihao, et al.
Published: (2025)