·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
America needs to stop getting shocked by Chinese AI2h◆Advancing next-gen AI with materials science innovation3h◆Gritt exits stealth with $34 million for robots to build solar plants—then, everything else3h◆Capacity and Redundancy Trade-offs in Multi-Task Learning9h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation9h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making9h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection9h◆Supervised Reward Inference9h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization9h◆Is Progressive Disclosure All You Need for Long-Context Agents?9h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability9h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification9h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration9h◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection9h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI9h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models9h◆Kernel Regression with Tensor Trains and Hadamard Overparameterization9h◆AI-Augmented Human Resource Management? Insights from German companies9h◆Diagnosing Correctness Probes under Self-Judgement Confounding9h◆BLAD: A Historically Contextualized, Multilingual Dataset of Bangladeshi Legal Acts (1799 to 2025)9h◆America needs to stop getting shocked by Chinese AI2h◆Advancing next-gen AI with materials science innovation3h◆Gritt exits stealth with $34 million for robots to build solar plants—then, everything else3h◆Capacity and Redundancy Trade-offs in Multi-Task Learning9h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation9h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making9h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection9h◆Supervised Reward Inference9h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization9h◆Is Progressive Disclosure All You Need for Long-Context Agents?9h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability9h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification9h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration9h◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection9h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI9h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models9h◆Kernel Regression with Tensor Trains and Hadamard Overparameterization9h◆AI-Augmented Human Resource Management? Insights from German companies9h◆Diagnosing Correctness Probes under Self-Judgement Confounding9h◆BLAD: A Historically Contextualized, Multilingual Dataset of Bangladeshi Legal Acts (1799 to 2025)9h◆
News/Looped State-Space Language Models with Adaptive Exit-State Selection
arxiv
PublishedJuly 14, 2026 at 4:00 AM
—neutral

Looped State-Space Language Models with Adaptive Exit-State Selection

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

arXiv:2607.10110v1 Announce Type: new Abstract: Recent work on looped language models suggests that many reasoning problems benefit from greater computational depth rather than from additional independent parameters. Existing studies, however, focus almost exclusively on Transformer backbones, leavi

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
arxivCapacity and Redundancy Trade-offs in Multi-Task Learning9harxivPredictive Training with Latent Imagination for Visual Quadruped Navigation9harxivWhere Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making9harxivDid We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection9h
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