·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Sequential Capacity of Quantum Processes with Finite Memory11h◆Q-MINO: A Minimal-Norm Method for Quantization-Aware Training11h◆Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning11h◆Model Merging via Data-Free Covariance Estimation11h◆Geometry-Dependent Bounds for Online Non-Monotone DR-Submodular Maximization11h◆Scaling Collider Event Generation with Residual-Quantized Tokens11h◆TANGO: Treating Tokens as Operators11h◆Oblivious Learning and Collusive Pricing11h◆Verification Pulses and the Cost of Escaping Wrong Consensus11h◆Attention Manifolds: Steering or Blocking Language Models by Editing Learned B-Spline Surfaces11h◆Stable and Counterfactually Robust Physical World Models from Imposed Structure and Learned Physics11h◆Benchmarking System One decision models against trained classifiers and language models for automated decision gates11h◆MoRA: MoE Pruning via Router Bias Learning and Expert Approximation11h◆M$^2$Weather: A Benchmark for Joint Multi-Station and Multi-Variable Weather Forecasting11h◆Metacognitive Reasoning in Energy Based Models using Instance Based Learning Theory11h◆EchoPress: Query-Agnostic KV Cache Pruning via Virtual Context Reconstruction11h◆Source Identification Is Not Fitness Testing: Measuring the Limits of Synthetic-Data Attribution11h◆CommunityKV: Efficient Long-Context Decoding via Graph Partitioning11h◆IrekoGPT: Turning Structured Pruning into Post-Hoc Slimmable LLMs11h◆Every Batch Is Its Own Validation Set: Leave-One-Out Gradient Matching for Online Data Selection in LLM Fine-Tuning11h◆Sequential Capacity of Quantum Processes with Finite Memory11h◆Q-MINO: A Minimal-Norm Method for Quantization-Aware Training11h◆Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning11h◆Model Merging via Data-Free Covariance Estimation11h◆Geometry-Dependent Bounds for Online Non-Monotone DR-Submodular Maximization11h◆Scaling Collider Event Generation with Residual-Quantized Tokens11h◆TANGO: Treating Tokens as Operators11h◆Oblivious Learning and Collusive Pricing11h◆Verification Pulses and the Cost of Escaping Wrong Consensus11h◆Attention Manifolds: Steering or Blocking Language Models by Editing Learned B-Spline Surfaces11h◆Stable and Counterfactually Robust Physical World Models from Imposed Structure and Learned Physics11h◆Benchmarking System One decision models against trained classifiers and language models for automated decision gates11h◆MoRA: MoE Pruning via Router Bias Learning and Expert Approximation11h◆M$^2$Weather: A Benchmark for Joint Multi-Station and Multi-Variable Weather Forecasting11h◆Metacognitive Reasoning in Energy Based Models using Instance Based Learning Theory11h◆EchoPress: Query-Agnostic KV Cache Pruning via Virtual Context Reconstruction11h◆Source Identification Is Not Fitness Testing: Measuring the Limits of Synthetic-Data Attribution11h◆CommunityKV: Efficient Long-Context Decoding via Graph Partitioning11h◆IrekoGPT: Turning Structured Pruning into Post-Hoc Slimmable LLMs11h◆Every Batch Is Its Own Validation Set: Leave-One-Out Gradient Matching for Online Data Selection in LLM Fine-Tuning11h◆
News/Benchmarking System One decision models against trained classifiers and language models for automated decision gates
arxiv
PublishedOctober 3, 2026 at 4:00 AM
—neutral

Benchmarking System One decision models against trained classifiers and language models for automated decision gates

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

arXiv:2610.00346v1 Announce Type: new Abstract: Software that hands branching decisions to a model needs a declared option and a probability it can threshold. Typed decision models, also called System One models, return such probabilities without generating text, while supervised classifiers and gen

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
arxivSequential Capacity of Quantum Processes with Finite Memory11harxivSentence Specificity Scores for Collaborative Technical Documentation: A Domain-Transfer Study11harxivQ-MINO: A Minimal-Norm Method for Quantization-Aware Training11harxivSmoothOperator: Enhancing Representations for Fine-grained Open-set Recognition via Modulated Label Smoothing11h
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 ↗
Built by Marouane Gazouzi
HomeModelsNews