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Xiaolong Zou

8 accepted papers

2026

Hippoformer: Integrating Hippocampus-inspired Spatial Memory with Transformers

ICLR 2026poster

Transformers form the foundation of modern generative AI, yet their key–value memory lacks inherent spatial priors, constraining their capacity for spatial reasoning. In contrast, neuroscience points to the hippocampal–entorhinal system, where the medial entorhinal cortex provides structural codes a…

Cited by 0SourcecodeScholar
2024

Continuous Rotation Group Equivariant Network Inspired by Neural Population Coding

AAAI 2024technical

Neural population coding can represent continuous information by neurons with a series of discrete preferred stimuli, and we find that the bell-shaped tuning curve plays an important role in this mechanism. Inspired by this, we incorporate a bell-shaped tuning curve into the discrete group convoluti…

Cited by 1SourcePDFScholar
2024

DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems

AAAI 2024technical

Attaining the equilibrium geometry of a catalyst-adsorbate system is key to fundamentally assessing its effective properties, such as adsorption energy. While machine learning methods with advanced representation or supervision strategies have been applied to boost and guide the relaxation processes…

2024

Leveraging Attractor Dynamics in Spatial Navigation for Better Language Parsing

ICML 2024spotlight

Increasing experimental evidence suggests that the human hippocampus, evolutionarily shaped by spatial navigation tasks, also plays an important role in language comprehension, indicating a shared computational mechanism for both functions. However, the specific relationship between the hippocampal…

Cited by 0SourcePDFScholar
2023

Learning and processing the ordinal information of temporal sequences in recurrent neural circuits

NeurIPS 2023poster

Temporal sequence processing is fundamental in brain cognitive functions. Experimental data has indicated that the representations of ordinal information and contents of temporal sequences are disentangled in the brain, but the neural mechanism underlying this disentanglement remains largely unclea…

Cited by 0SourcePDFScholar
2020

An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification

ECCV 2020poster

The progressive clustering method and its variants, which iteratively generate pseudo labels for unlabeled data and perform feature learning, have shown great process in unsupervised person re-identification (re-id). However, they have an intrinsic problem of modeling the in-camera variability of im…

Cited by 65SourcePDFScholar
2019

Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently

NeurIPS 2019poster

Experimental data has revealed that in addition to feedforward connections, there exist abundant feedback connections in a neural pathway. Although the importance of feedback in neural information processing has been widely recognized in the field, the detailed mechanism of how it works remains larg…