In plain words: They tested whether ordinary high-dimensional meaning spaces, with noise and competing memories, naturally show human memory effects. Forgetting matched the human curve (0.46 vs about 0.5) only when memories competed; without rivals it was about 50 times weaker, so time alone caused none.
Abstract
Why do we forget? Why do we remember things that never happened? The conventional answer points to biological hardware. We propose a different one: geometry. Here we show that high-dimensional embedding spaces, subjected to noise, interference, and temporal degradation, reproduce quantitative signatures of human memory with no phenomenon-specific engineering. Power-law forgetting ($b = 0.460 \pm 0.183$, human $b \approx 0.5$) arises from interference among competing memories, not from decay. The identical decay function without competitors yields $b \approx 0.009$, fifty times smaller. Time alone does not produce forgetting in this system. Competition does. Production embedding models (nominally 384--1{,}024 dimensions) concentrate their variance in only ${\sim}16$ effective dimensions, placing them deep in the interference-vulnerable regime. False memories require no engineering at all: cosine similarity on unmodified pre-trained embeddings reproduces the Deese--Roediger--McDermott false alarm rate ($0.583$ versus human ${\sim}0.55$) with zero parameter tuning and no boundary conditions. We did not build a false memory system. We found one already present in the raw geometry of semantic space. These results suggest that core memory phenomena are not bugs of biological implementation but features of any system that organizes information by meaning and retrieves it by proximity.
Sambartha Ray Barman, Andrey Starenky, Sophia Bodnar, Nikhil Narasimhan, Ashwin Gopinath
arXiv:2604.06222 · q-bio.NC, cs.AI, cs.IR, cs.NE · submitted Mar 27, 2026
abstract · pdf · html
Uncalled for riff on the synopsis:
The conundrum of forgetting comes seems to come down to a gradient of persistence, whereby new stimulus prevails over memories.
If it didn't, the organism sensorium would be a captive to memories, which once noted seems like an obviously maladaptive dynamic.
Resolved: Perfect memory would preclude your sensory awareness...
So the next question is why does the gradient of persistence have such a shape / slope?
The dynamic of knowing vs. perceiving looks like some tradeoff over persistence and speed of access (a la caching).
Are memories something like deferred stimuli?
Thought must be some other domain within this gradient, subject to other dynamics?
What structures of the blob of protoplasm which is the brain manifest as Euclidian geometry, phonetic language / alphabet, and Turing machines? How does something so mushy give rise to such rigidity... which in turn bizarrely can model mushiness. Almost like an error condition.
Stimulating, guess will have to read the paper!