Papers › An Algorithm for Routing Vectors in Sequences

An Algorithm for Routing Vectors in Sequences

20 Nov 2022arXiv:2211.11754archive 2025-07-28

Franz A. Heinsen

We propose a routing algorithm that takes a sequence of vectors and computes a new sequence with specified length and vector size. Each output vector maximizes "bang per bit," the difference between a net benefit to use and net cost to ignore data, by better predicting the input vectors. We describe output vectors as geometric objects, as latent variables that assign credit, as query states in a model of associative memory, and as agents in a model of a Society of Mind. We implement the algorithm with optimizations that reduce parameter count, computation, and memory use by orders of magnitude, enabling us to route sequences of greater length than previously possible. We evaluate our implementation on natural language and visual classification tasks, obtaining competitive or state-of-the-art accuracy and end-to-end credit assignments that are interpretable.

PaperPDFCode

Code

glassroom/heinsen_routing officialmentioned in papermentioned on GitHubpytorchMIT report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Image ClassificationSentiment AnalysisText Classification

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Classification CIFAR-10 Heinsen Routing + BEiT-large 16 224 Percentage correct 99.2 #11 of 265 Archive leaderboard report
Image Classification CIFAR-100 Heinsen Routing + BEiT-large 16 224 PARAMS 309.8M #7 of 211 Archive leaderboard report
Image Classification CIFAR-100 Heinsen Routing + BEiT-large 16 224 Percentage correct 93.8 #7 of 211 Archive leaderboard report
Image Classification ImageNet Heinsen Routing + BEiT-large 16 224 Number of params 312.8M #130 of 1060 Archive leaderboard report
Image Classification ImageNet Heinsen Routing + BEiT-large 16 224 Top 1 Accuracy 86.7% #130 of 1060 Archive leaderboard report
Sentiment Analysis IMDb Heinsen Routing + RoBERTa Large Accuracy 96.2 #4 of 49 Archive leaderboard report
Sentiment Analysis SST-2 Binary classification Heinsen Routing + RoBERTa-large Accuracy 96.0 #21 of 87 Archive leaderboard report
Sentiment Analysis SST-5 Fine-grained classification Heinsen Routing + RoBERTa Large Accuracy 59.8 #2 of 31 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections