Cover Image

From Model Training to Model Raising

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aydin, Roland, Cyron, Christian, Bachelor, Steve, Anderson, Ashton, West, Robert
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Computers and Society Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The AI Alignment Paradox
by: West, Robert, et al.
Published: (2024)

Assessing Social Alignment: Do Personality-Prompted Large Language Models Behave Like Humans?
by: Zakazov, Ivan, et al.
Published: (2024)

Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
by: Hamade, Karim, et al.
Published: (2024)

Training Foundation Models as Data Compression: On Information, Model Weights and Copyright Law
by: Franceschelli, Giorgio, et al.
Published: (2024)

Fleet of Agents: Coordinated Problem Solving with Large Language Models
by: Klein, Lars, et al.
Published: (2024)

A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents
by: Vassoyan, Jean, et al.
Published: (2024)

Moderating Model Marketplaces: Platform Governance Puzzles for AI Intermediaries
by: Gorwa, Robert, et al.
Published: (2023)

From Data to Behavior: Predicting Unintended Model Behaviors Before Training
by: Wang, Mengru, et al.
Published: (2026)

I Prefer not to Say: Protecting User Consent in Models with Optional Personal Data
by: Leemann, Tobias, et al.
Published: (2022)

Epistemic diversity across language models mitigates knowledge collapse
by: Hodel, Damian, et al.
Published: (2025)

Enhancing Equitable Access to AI in Housing and Homelessness System of Care through Federated Learning
by: Taib, Musa, et al.
Published: (2024)

Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
by: Zhu, Zhaowei, et al.
Published: (2023)

From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap
by: Kou, Tianqi
Published: (2024)

In-class Data Analysis Replications: Teaching Students while Testing Science
by: Gligoric, Kristina, et al.
Published: (2023)

Building a Domain-specific Guardrail Model in Production
by: Niknazar, Mohammad, et al.
Published: (2024)

The Amazon Nova Family of Models: Technical Report and Model Card
by: AGI, Amazon, et al.
Published: (2025)

Generative AI Training and Copyright Law
by: Stober, Sebastian, et al.
Published: (2025)

On the Cause of Unfairness: A Training Sample Perspective
by: Yao, Yuanshun, et al.
Published: (2023)

Towards Detecting Persuasion on Social Media: From Model Development to Insights on Persuasion Strategies
by: Meguellati, Elyas, et al.
Published: (2025)

AI Fairness Beyond Complete Demographics: Current Achievements and Future Directions
by: Wang, Zichong, et al.
Published: (2025)

Towards Sustainability Model Cards
by: Jouneaux, Gwendal, et al.
Published: (2025)

Sabotage Evaluations for Frontier Models
by: Benton, Joe, et al.
Published: (2024)

Foundation Model Transparency Reports
by: Bommasani, Rishi, et al.
Published: (2024)

Adapting Mental Health Prediction Tasks for Cross-lingual Learning via Meta-Training and In-context Learning with Large Language Model
by: Lifelo, Zita, et al.
Published: (2024)

The 2025 Foundation Model Transparency Index
by: Wan, Alexander, et al.
Published: (2025)

On Catastrophic Inheritance of Large Foundation Models
by: Chen, Hao, et al.
Published: (2024)

The 2024 Foundation Model Transparency Index
by: Bommasani, Rishi, et al.
Published: (2024)

Harm Amplification in Text-to-Image Models
by: Hao, Susan, et al.
Published: (2024)

The Representational Status of Deep Learning Models
by: Duede, Eamon
Published: (2023)

On the Societal Impact of Open Foundation Models
by: Kapoor, Sayash, et al.
Published: (2024)

The Metaphysics We Train: A Heideggerian Reading of Machine Learning
by: Shakeri, Heman
Published: (2025)

AdvKT: An Adversarial Multi-Step Training Framework for Knowledge Tracing
by: Fu, Lingyue, et al.
Published: (2025)

On Fairness of Low-Rank Adaptation of Large Models
by: Ding, Zhoujie, et al.
Published: (2024)

Ecosystem Graphs: The Social Footprint of Foundation Models
by: Bommasani, Rishi, et al.
Published: (2023)

Addressing Label Leakage in Knowledge Tracing Models
by: Badran, Yahya, et al.
Published: (2024)

Building Interpretable Models for Moral Decision-Making
by: Goel, Mayank, et al.
Published: (2026)

Unified Uncertainty Estimation for Cognitive Diagnosis Models
by: Wang, Fei, et al.
Published: (2024)

FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
by: Cong, Zicun, et al.
Published: (2024)

Explaining How Quantization Disparately Skews a Model
by: Bellam, Abhimanyu, et al.
Published: (2025)

Holistically Evaluating the Environmental Impact of Creating Language Models
by: Morrison, Jacob, et al.
Published: (2025)