Preprint2026
Neural Scaling Laws and Science Without Theory
Unknown
This paper critically examines the relationship between neural scaling laws and the role of theory in machine learning science.
0Jan 1, 2026Scaling Laws
AI Research
AI & ML Research Papers
A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
All Papers
27 papersPreprint2023
Science in the age of large language models
Unknown
This paper examines how large language models are transforming scientific research and discusses the opportunities and challenges they present for the scientific community.
0Jan 1, 2023Large Language Models
PreprintarXiv.org2024
Challenges and Responses in the Practice of LLMs
Hongyin Zhu
This paper systematically categorizes and answers practical questions about LLMs across five dimensions: computing power, software architecture, data, applications, and brain science.
1Aug 18, 2024
arXiv
Preprint2026
AI for science: Progress, challenges, and perspectives
Unknown
This review systematically evaluates AI4Science's progress, highlighting the shift from text-centric generation to reasoning-oriented intelligence and its challenges and perspectives.
0Jan 1, 2026Reasoning
Preprint2024
Accelerating AI for science: open data science for science
Unknown
This paper presents a research agenda for AI for science, focusing on building technical foundations to leverage data for scientific discovery.
0Jan 1, 2024
Preprint2025
From ai for science to agentic science: A survey on autonomous scientific discovery
Unknown
This paper introduces Agentic Science as a new stage in AI for Science, tracing its evolution and identifying five core capabilities for autonomous scientific discovery.
0Aug 1, 2025
arXiv
Preprint2020
AI for Science
Unknown
The paper discusses the shift from traditional storage systems to in situ AI that provides multi-level abstractions for accessing information content from raw bits to learned functions capturing distributions.
0Jan 1, 2020
Preprint2022
Graph neural networks for materials science and chemistry
Unknown
This paper provides a comprehensive overview of graph neural networks applied to materials science and chemistry, outlining potential tasks and methodologies.
0Jan 1, 2022Neural Networks
Preprint2024
Graph neural networks
Unknown
This paper provides a comprehensive overview of graph neural networks (GNNs), highlighting their flexibility in representing diverse knowledge domains, particularly in life sciences.
0Jan 1, 2024Neural Networks
Preprint2024
Marrying causal representation learning with dynamical systems for science
Unknown
This paper integrates causal representation learning with dynamical systems to model scientific phenomena, framing the problem as a causal representation learning task.
0Jan 1, 2024
Preprint2021
Meta-learning in natural and artificial intelligence
Unknown
This paper surveys meta-learning across natural and artificial intelligence, highlighting recent developments in neuroscience and machine learning.
0Jan 1, 2021
Preprint2026
EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents
Luigi Sigillo, Matteo Silvestri, Francesco Tabaro, et al.
EMBL AI Librarian is a knowledge layer that lets AI agents query life-sciences literature in natural language and receive evidence, improving performance across multiple benchmarks.
0Jul 30, 2026Retrieval Augmented GenerationBenchmarks
arXiv