The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Recent generations of frontier language models have introduced Large Reasoning Models (LRMs) that generate detailed…
Category: Machine Learning
Checklists Are Better Than Reward Models For Aligning Language Models
Language models must be adapted to understand and follow user instructions. Reinforcement learning is widely…
Generative and Contrastive Graph Representation Learning
Self-supervised learning (SSL) on graphs generates node and graph representations (i.e., embeddings) that can be…
PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors
We revisit the problem of secure aggregation of high-dimensional vectors in a two-server system such…
Why and When to Use Sentence Embeddings Over Word Embeddings
Choosing the right text representation is a critical first step in any natural language processing…
Golf champ Bryson DeChambeau is partnering with Google Cloud to explore AI and sports performance.
Bryson DeChambeau is kicking off a partnership with Google Cloud to expand his AI aspirations.
PersonaTeaming: Exploring How Introducing Personas Can Improve Automated AI Red-Teaming
This paper was accepted at the Workshop on Regulatable ML (ReML) at NeurIPS 2025. Recent…
Scaling Laws for Optimal Data Mixtures
Large foundation models are typically trained on data from multiple domains, with the data mixture—the…
AI system learns from many types of scientific information and runs experiments to discover new materials
The new “CRESt” platform could help find solutions to real-world energy problems that have plagued…