ArticleNature communications2025
Adaptive spatial-temporal information processing based on in-memory attention-inspired devices.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Wafer-scale 2D semimetal heterostructures enabling mid-infrared motion tracking with in-sensor perceptual compression.Science advances · 2026Article
- Coexisting Volatile and Nonvolatile Switching in 3D ALD-IGZO Vertical RRAM for Fully Hardware-Based Wide Reservoir Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Neuromorphic In-Memory Computing for Marine Visual-Auditory Perception.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- A Chemically Programmable Retinomorphic GaN p-n Diode for Multimode Visual Sensing.Advanced materials (Deerfield Beach, Fla.) · 2026Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatial-temporal information perception is widely used for motion processing in dynamic scenes, but present technology requires relatively huge hardware resource consumption. The attention mechanism helps the human brain extract required information from tremendous data at a low cost. Here, we propose an attention-inspired artificial intelligence architecture based on hetero-dimensional modulations between zero-dimensional contact and two-dimensional electrostatic interfaces. An adaptive spatial-temporal information processing primitive is successfully implemented based on in-memory analog computing. Experiments of attention adjustments responding to different situations validate the adaptation capability to environmental changes. A demonstration of 5×5-unit data stream processing is conducted, and intensities of spatial and temporal information are varied with attention distribution from 0% to 100%. The attention-inspired device is applied to autonomous driving edge intelligence scenarios, showing high adaptability to traffic scene variations. The proposed architecture exhibits a tens-fold latency reduction, hundreds-fold area improvement, and thousands-fold energy saving compared to the conventional transistor-based circuit.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.