ICLR 2026PastOther
New Frontiers in Associative Memories - Workshop at ICLR 2026
NFAM 2026
- Submission deadline
- Feb 15, 2026, 11:59 UTCOpenReview-synced 2026-02-15 11:59 UTC (as of 2026-06-23) — extensions on OpenReview are applied automatically; verify on the website.
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (42)
Fetched from OpenReview (v2) on 2026-06-10.
A Dynamical Theory of Sequential Retrieval in Input-Driven Hopfield Networks
Adaptive Associative Memory with Differentiable Content-Addressable Memories for Online Learning
Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness
ASSOCIATIVE RETRIEVAL AS TEST-TIME OPTIMIZATION IN TRANSFORMER ATTENTION
Boltzmann Routing for Energy-Compatible Mixture of Experts
Can Local Energy Geometry Predict Per-Pattern Retrieval Reliability in Dense Associative Memories?
Continuous-Time Heteroassociative Memory at Biological Timescales
Deep Neural Networks as Finite-Step Hopfield Dynamics
Dense Associative Memories with Analog Circuits
Dense Associative Memory for Gaussian Distributions
Dyadic Learning in Asymmetric ConvNets
Dynamics of modern Hopfield networks
Energy Landscapes of Truthfulness in LLM Attention
Energy Minimization for Training Dense Associative Memory
EnergyMap: Unraveling the Data Manifold with Energy-based Dimensionality Reduction
Extending LLM Context via Associative Recurrent Memory
Generative Associative Memory via Equilibrium Matching
GradMem: Learning to Write Context into Memory with Test-Time Gradient Descent
Graph Hopfield Networks: Energy-Based Node Classification with Associative Memory
Interdomain Attention: Beyond Token-Level Key-Value Memory
Intrinsic Dense Associative Memory on Riemannian Manifolds
Language Diffusion Models are Associative Memories
Learning to learn dynamical associations with reward-gated local plasticity
Mixture of Chapters: Scaling Learnt Memory in Transformers
On low-dimensional representations and associative memory energy functions
Optimizing Remasking Schedules for Reasoning in Discrete Diffusion Models
Parallel Manifold Steering: Efficient Adaptation of Large Associative Memories via Residual Energy Shaping
Plan-Aware Automated Context Engineering
Power-law feature statistics explain test reconstruction gaps in Associative Memories
Reasoning as Attractor Dynamics: Latent Memory Retrieval via Gibbs-Weighted Energy Minimization
Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion
Sharp storage capacity of a simplified model of linear associative memory
Sinkhorn based Associative Memory retrieval using Spherical Hellinger Kantorovich dynamics
Sparse Associative Memories Through the Lens of Compact Kernel Regression
TACE: Token-Aware Chunked Encoding
The Key to State Reduction in Linear Attention: A Rank-based Perspective
Thermal Robustness of Retrieval in Dense Associative Memories: LSE vs LSR Kernels
Thermodynamic Binding: Freezing Chimeric States in Multi-Modal Associative Memories
To Keep or to Forget: Toward Context-Sensitive Memory in Large Language Models
Towards Context-Based Retrieval in Associative Memories
Training a Convergent Energy Transformer with Equilibrium Propagation
When Memories Collide: Associative Interference Dynamics in Lifelong Agent Memory