Amortizing Maximum Inner Product Search with Learned Support Functions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Olausson, Theo X., Monteiro, João, Klein, Michal, Cuturi, Marco
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Nectar: Neural Estimation of Cached-Token Attention via Regression
by: Monteiro, João, et al.
Published: (2026)

Learning Unmasking Policies for Diffusion Language Models
by: Jazbec, Metod, et al.
Published: (2025)

GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics
by: Klein, Dominik, et al.
Published: (2023)

Multivariate Conformal Prediction using Optimal Transport
by: Klein, Michal, et al.
Published: (2025)

Contrasting Multiple Representations with the Multi-Marginal Matching Gap
by: Piran, Zoe, et al.
Published: (2024)

On Fitting Flow Models with Large Sinkhorn Couplings
by: Zhang, Stephen, et al.
Published: (2025)

Stochastic KV Routing: Enabling Adaptive Depth-Wise Cache Sharing
by: Filippova, Anastasiia, et al.
Published: (2026)

Flow Matching with Semidiscrete Couplings
by: Mousavi-Hosseini, Alireza, et al.
Published: (2025)

HyperTransport: Amortized Conditioning of T2I Generative Models
by: Maiorca, Valentino, et al.
Published: (2026)

Learning Elastic Costs to Shape Monge Displacements
by: Klein, Michal, et al.
Published: (2023)

Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search
by: Bruch, Sebastian, et al.
Published: (2024)

Careful with that Scalpel: Improving Gradient Surgery with an EMA
by: Hsieh, Yu-Guan, et al.
Published: (2024)

DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures
by: Gualdoni, Eleonora, et al.
Published: (2026)

On a Neural Implementation of Brenier's Polar Factorization
by: Vesseron, Nina, et al.
Published: (2024)

Progressive Entropic Optimal Transport Solvers
by: Kassraie, Parnian, et al.
Published: (2024)

Amortized Active Learning for Nonparametric Functions
by: Li, Cen-You, et al.
Published: (2024)

The Data-Quality Illusion: Rethinking Classifier-Based Quality Filtering for LLM Pretraining
by: Saada, Thiziri Nait, et al.
Published: (2025)

Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
by: Fuchs, Tobias, et al.
Published: (2025)

Disentangled Representation Learning with the Gromov-Monge Gap
by: Uscidda, Théo, et al.
Published: (2024)

Completed Hyperparameter Transfer across Modules, Width, Depth, Batch and Duration
by: Mlodozeniec, Bruno, et al.
Published: (2025)

Learning Decision Trees as Amortized Structure Inference
by: Mahfoud, Mohammed, et al.
Published: (2025)

Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures
by: Vesseron, Nina, et al.
Published: (2025)

The Geometries of Truth Are Orthogonal Across Tasks
by: Azizian, Waiss, et al.
Published: (2025)

A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models
by: Olausson, Theo X., et al.
Published: (2026)

LILO: Learning Interpretable Libraries by Compressing and Documenting Code
by: Grand, Gabriel, et al.
Published: (2023)

Simple ReFlow: Improved Techniques for Fast Flow Models
by: Kim, Beomsu, et al.
Published: (2024)

k-Maximum Inner Product Attention for Graph Transformers and the Expressive Power of GraphGPS
by: De Schouwer, Jonas, et al.
Published: (2026)

Locking Pretrained Weights via Deep Low-Rank Residual Distillation
by: Sakamoto, Keitaro, et al.
Published: (2026)

Self-Refining Training for Amortized Density Functional Theory
by: Hassan, Majdi, et al.
Published: (2025)

A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
by: Lin, Tianyi, et al.
Published: (2023)

Latent Geometry Beyond Search: Amortizing Planning in World Models
by: Nguyen, Hoang, et al.
Published: (2026)

The Design Space of Tri-Modal Masked Diffusion Models
by: Bethune, Louis, et al.
Published: (2026)

Amortized Sampling with Transferable Normalizing Flows
by: Tan, Charlie B., et al.
Published: (2025)

The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
by: Gu, Alex, et al.
Published: (2024)

Unsupervised Continual Learning for Amortized Bayesian Inference
by: Mishra, Aayush, et al.
Published: (2026)

The Coupling Within: Flow Matching via Distilled Normalizing Flows
by: Berthelot, David, et al.
Published: (2026)

Improving Relative Representations with Learned Anchors and Whitened Inner Products
by: Svendsen, Oscar Thorsted, et al.
Published: (2026)

Amortized Bayesian Workflow
by: Li, Chengkun, et al.
Published: (2024)

Memory-Amortized Inference: A Topological Unification of Search, Closure, and Structure
by: Li, Xin
Published: (2025)

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning
by: Audiffren, Julien, et al.
Published: (2026)