Programs-of-Layers in LLMs through the Lens of Cortical Areas
cs.AI
Submitted: 2026-09-25
Updated: 2026-09-25
Code: https://github.com/tianyi-lab/PoLAr
Project page: https://datexis.github.io/RE-PoLar
Terminology
Sources
- Scalable Machines with Intrinsic Higher Mental-State Dynamics
- Mixture of Cognitive Reasoners: Modular Reasoning with Brain-Like Specialization
- Is One Layer Enough? Understanding Inference Dynamics in Tabular Foundation Models
- Memory Layers at Scale
- Continuous Thought Machines
- Reducing Transformer Depth on Demand with Structured Dropout
- Looped Transformers for Length Generalization
- Coordination Among Neural Modules Through a Shared Global Workspace
- HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
- Router-Tuning: A Simple and Effective Approach for Enabling Dynamic-Depth in Transformers
- Dr.LLM: Dynamic Layer Routing in LLMs
- From Noise to Diversity: Random Embedding Injection in LLM Reasoning
- The Neuroscience of Transformers
- What Layers When: Learning to Skip Compute in LLMs with Residual Gates
- Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs
- Adaptive Layer-skipping in Pre-trained LLMs
- Let's Think Dot by Dot: Hidden Computation in Transformer Language Models
- Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
- Representational Alignment Across Model Layers and Brain Regions with Multi-Level Optimal Transport
- Meaningless Tokens, Meaningful Gains: How Activation Shifts Enhance LLM Reasoning
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
- VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection