·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
SFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning1h◆MSTN: A Lightweight and Fast Model for General TimeSeries Analysis1h◆Optical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning1h◆Dynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models1h◆Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents1h◆GIPO: Gaussian Importance Sampling Policy Optimization1h◆Specialization of softmax attention heads: insights from the high-dimensional single-location model1h◆On the Robustness of Langevin Dynamics to Score Function Error1h◆Level Up: Defining and Exploiting Transitional Problems for Curriculum Learning1h◆LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels1h◆From Causal Discovery to Dynamic Causal Inference in Neural Time Series1h◆Why Muon Outperforms Adam: A Curvature Perspective1h◆Vision Hopfield Memory Networks1h◆Provably Auditable and Safe LLM Agents from Human-Authored Ontologies1h◆Algebraic Diversity: Group-Theoretic Spectral Estimation from Single Observations1h◆Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains1h◆SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling1h◆The Topological Trouble With Transformers1h◆Adaptive Head Budgeting for Efficient Multi-Head Attention1h◆Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs1h◆SFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning1h◆MSTN: A Lightweight and Fast Model for General TimeSeries Analysis1h◆Optical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning1h◆Dynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models1h◆Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents1h◆GIPO: Gaussian Importance Sampling Policy Optimization1h◆Specialization of softmax attention heads: insights from the high-dimensional single-location model1h◆On the Robustness of Langevin Dynamics to Score Function Error1h◆Level Up: Defining and Exploiting Transitional Problems for Curriculum Learning1h◆LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels1h◆From Causal Discovery to Dynamic Causal Inference in Neural Time Series1h◆Why Muon Outperforms Adam: A Curvature Perspective1h◆Vision Hopfield Memory Networks1h◆Provably Auditable and Safe LLM Agents from Human-Authored Ontologies1h◆Algebraic Diversity: Group-Theoretic Spectral Estimation from Single Observations1h◆Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains1h◆SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling1h◆The Topological Trouble With Transformers1h◆Adaptive Head Budgeting for Efficient Multi-Head Attention1h◆Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs1h◆
News/Neuron Populations Exhibit Divergent Selectivity with Scale
arxiv
PublishedJune 3, 2026 at 4:00 AM

Neuron Populations Exhibit Divergent Selectivity with Scale

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2606.03990v1 Announce Type: cross Abstract: We investigate whether neuron populations within neural networks evolve predictably with scale, extending scaling laws beyond macroscopic observables such as loss. To probe this question, we study Rosetta Neurons, a previously characterized class of

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning1harxivMSTN: A Lightweight and Fast Model for General TimeSeries Analysis1harxivOptical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning1harxivDynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models1h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews