Imagen de Portada

On the Origin of Algorithmic Progress in AI

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gundlach, Hans, Fogelson, Alex, Lynch, Jayson, Trisovic, Ana, Rosenfeld, Jonathan, Sandhu, Anmol, Thompson, Neil
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence 68T07, 68Q25 I.2.6
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Quantum Deep Learning Still Needs a Quantum Leap
por: Gundlach, Hans, et al.
Publicado: (2025)

The Price of Progress: Price Performance and the Future of AI
por: Gundlach, Hans, et al.
Publicado: (2025)

Advances in Set Function Learning: A Survey of Techniques and Applications
por: Xie, Jiahao, et al.
Publicado: (2025)

Backpropagation Through Time For Networks With Long-Term Dependencies
por: Bird, George, et al.
Publicado: (2021)

Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness
por: Gaikwad, Madhava
Publicado: (2026)

Graded Transformers
por: Shaska Sr, Tony
Publicado: (2025)

QGraphLIME - Explaining Quantum Graph Neural Networks
por: Jena, Haribandhu, et al.
Publicado: (2025)

The Inhibitor: ReLU and Addition-Based Attention for Efficient Transformers under Fully Homomorphic Encryption on the Torus
por: Brännvall, Rickard, et al.
Publicado: (2023)

"Abuse Risks are Often Inherent to Product Features": Exploring AI Vendors' Bug Bounty and Responsible Disclosure Policies
por: Piao, Yangheran, et al.
Publicado: (2025)

Explainable Attention-Based LSTM Framework for Early Detection of AI-Assisted Ransomware via File System Behavioral Analysis
por: Nayak, Prabhudarshi, et al.
Publicado: (2026)

From Features to Graphs: Exploring Graph Structures and Pairwise Interactions via GNNs
por: Yamchote, Phaphontee, et al.
Publicado: (2025)

Tricks and Plug-ins for Gradient Boosting with Transformers
por: Fang, Biyi, et al.
Publicado: (2025)

Understanding the Nature of Generative AI as Threshold Logic in High-Dimensional Space
por: Levin, Ilya
Publicado: (2026)

ARF-RLHF: Adaptive Reward-Following for RLHF through Emotion-Driven Self-Supervision and Trace-Biased Dynamic Optimization
por: Zhang, YuXuan
Publicado: (2025)

Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
por: Mitchell, Rupert, et al.
Publicado: (2025)

Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
por: Lai, Guannan, et al.
Publicado: (2025)

Step-Aware Residual-Guided Diffusion for EEG Spatial Super-Resolution
por: Liu, Hongjun, et al.
Publicado: (2025)

Semantic Reward Collapse and the Preservation of Epistemic Integrity in Adaptive AI Systems
por: Parris, William
Publicado: (2026)

SafeAgent: Safeguarding LLM Agents via an Automated Risk Simulator
por: Zhou, Xueyang, et al.
Publicado: (2025)

Correction and Corruption: A Two-Rate View of Error Flow in LLM Protocols
por: Reitich, Fernando
Publicado: (2026)

Distinguished In Uniform: Self Attention Vs. Virtual Nodes
por: Rosenbluth, Eran, et al.
Publicado: (2024)

NOTAI.AI: Explainable Detection of Machine-Generated Text via Curvature and Feature Attribution
por: Breneur, Oleksandr Marchenko, et al.
Publicado: (2026)

Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents
por: Ma, Minghui, et al.
Publicado: (2026)

Evaluating Model-Agnostic Meta-Learning on MetaWorld ML10 Benchmark: Fast Adaptation in Robotic Manipulation Tasks
por: Atamuradov, Sanjar
Publicado: (2025)

Teaching and Learning under Deductive Errors
por: Telle, Jan Arne, et al.
Publicado: (2026)

Binarized Neural Networks Converge Toward Algorithmic Simplicity: Empirical Support for the Learning-as-Compression Hypothesis
por: Sakabe, Eduardo Y., et al.
Publicado: (2025)

The Serial Scaling Hypothesis
por: Liu, Yuxi, et al.
Publicado: (2025)

On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
por: Li, Zhong, et al.
Publicado: (2020)

Verifiable Fine-Tuning for LLMs: Zero-Knowledge Training Proofs Bound to Data Provenance and Policy
por: Akgul, Hasan, et al.
Publicado: (2025)

Theoretical Analysis of Positional Encodings in Transformer Models: Impact on Expressiveness and Generalization
por: Li, Yin
Publicado: (2025)

ProactBench: Beyond What The User Asked For
por: Harfi, Sepehr, et al.
Publicado: (2026)

A V2X-based Privacy Preserving Federated Measuring and Learning System
por: Alekszejenkó, Levente, et al.
Publicado: (2024)

The two clocks and the innovation window: When and how generative models learn rules
por: Wang, Binxu, et al.
Publicado: (2026)

cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series
por: Giannini, Federico, et al.
Publicado: (2026)

Harnessing non-adversarial robustness in large language models
por: Zhou, Qinghua, et al.
Publicado: (2026)

Safety, Security, and Cognitive Risks in World Models
por: Parmar, Manoj
Publicado: (2026)

Deep Hedging Under Non-Convexity: Limitations and a Case for AlphaZero
por: Maggiolo, Matteo, et al.
Publicado: (2025)

Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3
por: Nitarach, Natapong
Publicado: (2026)

Stage-wise Dynamics of Classifier-Free Guidance in Diffusion Models
por: Jin, Cheng, et al.
Publicado: (2025)

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
por: Helli, Kai, et al.
Publicado: (2024)