Image de couverture de livre

The Propensity for Density in Feed-forward Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Schoots, Nandi, Jackson, Alex, Kholmovaia, Ali, McBurney, Peter, Shanahan, Murray
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Training Neural Networks for Modularity aids Interpretability
par: Golechha, Satvik, et autres
Publié: (2024)

Decoding Communications with Partial Information
par: Cope, Dylan, et autres
Publié: (2025)

Learning Translations: Emergent Communication Pretraining for Cooperative Language Acquisition
par: Cope, Dylan, et autres
Publié: (2024)

Still "Talking About Large Language Models": Some Clarifications
par: Shanahan, Murray
Publié: (2024)

Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks
par: Schoots, Nandi, et autres
Publié: (2025)

The Topos of Transformer Networks
par: Villani, Mattia Jacopo, et autres
Publié: (2024)

Studying Cross-cluster Modularity in Neural Networks
par: Golechha, Satvik, et autres
Publié: (2025)

Existential Conversations with Large Language Models: Content, Community, and Culture
par: Shanahan, Murray, et autres
Publié: (2024)

Extending Activation Steering to Broad Skills and Multiple Behaviours
par: van der Weij, Teun, et autres
Publié: (2024)

Soft Contamination Means Benchmarks Test Shallow Generalization
par: Spiesberger, Ari, et autres
Publié: (2026)

A Closed-form Solution for Weight Optimization in Fully-connected Feed-forward Neural Networks
par: Tomic, Slavisa, et autres
Publié: (2024)

Dissecting Language Models: Machine Unlearning via Selective Pruning
par: Pochinkov, Nicholas, et autres
Publié: (2024)

PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach
par: Sehwag, Udari Madhushani, et autres
Publié: (2025)

Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers
par: Chen, Lei, et autres
Publié: (2024)

Transformers Use Causal World Models in Maze-Solving Tasks
par: Spies, Alex F., et autres
Publié: (2024)

Capabilities Ain't All You Need: Measuring Propensities in AI
par: Romero-Alvarado, Daniel, et autres
Publié: (2026)

On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning
par: Sun, Haoyuan, et autres
Publié: (2025)

Epistemically-guided forward-backward exploration
par: Urpí, Núria Armengol, et autres
Publié: (2025)

One Mask to Rule Them All: On Hidden Facts after Editing and How to Find Them
par: Holmov, Ali, et autres
Publié: (2026)

On the generalization of language models from in-context learning and finetuning: a controlled study
par: Lampinen, Andrew K., et autres
Publié: (2025)

Preferential subspace identification (PSID) with forward-backward smoothing
par: Sani, Omid G., et autres
Publié: (2025)

Lookbehind-SAM: k steps back, 1 step forward
par: Mordido, Gonçalo, et autres
Publié: (2023)

Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities
par: Xie, Ziwen, et autres
Publié: (2026)

Optimizing Dense Feed-Forward Neural Networks
par: Balderas, Luis, et autres
Publié: (2023)

Simulacra as Conscious Exotica
par: Shanahan, Murray
Publié: (2024)

Palatable Conceptions of Disembodied Being
par: Shanahan, Murray
Publié: (2025)

Enhancing Customer Service Chatbots with Context-Aware NLU through Selective Attention and Multi-task Learning
par: Nandi, Subhadip, et autres
Publié: (2025)

Mimicry and the Emergence of Cooperative Communication
par: Cope, Dylan, et autres
Publié: (2024)

Feed-Forward Optimization With Delayed Feedback for Neural Network Training
par: Flügel, Katharina, et autres
Publié: (2023)

Sobolev Space Regularised Pre Density Models
par: Kozdoba, Mark, et autres
Publié: (2023)

Generative Modeling with Flow-Guided Density Ratio Learning
par: Heng, Alvin, et autres
Publié: (2023)

Enhanced Generative Model Evaluation with Clipped Density and Coverage
par: Salvy, Nicolas, et autres
Publié: (2025)

Beyond Demand Estimation: Consumer Surplus Evaluation via Cumulative Propensity Weights
par: Bian, Zeyu, et autres
Publié: (2026)

Deep-layer limit and stability analysis of the basic forward-backward-splitting induced network (II): learning problems
par: Lin, Xuan, et autres
Publié: (2026)

Adaptive Transformer Modelling of Density Function for Nonparametric Survival Analysis
par: Zhang, Xin, et autres
Publié: (2024)

Contrastive Entropy Bounds for Density and Conditional Density Decomposition
par: Hu, Bo, et autres
Publié: (2025)

FLoRA: Fused forward-backward adapters for parameter efficient fine-tuning and reducing inference-time latencies of LLMs
par: Gowda, Dhananjaya, et autres
Publié: (2025)

Enhancing Fast Feed Forward Networks with Load Balancing and a Master Leaf Node
par: Charalampopoulos, Andreas, et autres
Publié: (2024)

Dynamic sparsity in tree-structured feed-forward layers at scale
par: Sedghi, Reza, et autres
Publié: (2026)

An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving
par: Villuri, Gnaneswar, et autres
Publié: (2024)