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#computer vision Preprint Oct 2026

VELD-QA: A Large-Scale Dataset for Visual Evidence Grounding and Question Answering in Long Documents

Existing long-document QA benchmarks rarely combine large-scale human-authored questions with detailed visual evidence annotations, limiting diagnosis of evidence localization and interpretation failures. We present VELD-QA, a large-scale benchmark for Visual Evidence grounding and question answering in Long Documents....

Zhivar Sourati, Marianne Menglin Liu, Rong Wang et al. · 0 citations
Preprint Aug 2026

Fuzzy-MoE: Interpretable Regime-Conditioned Expert Routing for Non-Stationary Multivariate Time Series Forecasting

In non-stationary multivariate time series, different variables and samples often exhibit heterogeneous latent dynamic states, while existing deep forecasting models usually compress them into a unified end-to-end mapping, leading to suboptimal modeling of time-varying dynamics and limited interpretability regarding wh...

Lan Guo, Jie Xiao, Zhao Su et al. · 0 citations
Open access Sep 2026

A High-Throughput Memory Compression Architecture for Real-Time 3D Visual Tracking and Quantification on Edge Devices

The deployment of real-time three-dimensional (3D) visual perception, continuous spatial sensing, and graphics-intensive multimedia applications on embedded edge devices introduces substantial runtime memory pressure. During execution, these workloads continuously generate small-granularity memory pages, including imag...

Yan-Bo Cheng, Lan Guo, Rui Zhou et al. · 0 citations
#machine learning Preprint Sep 2026

LLN: Learnable Lens Networks for Parameter-Efficient Long-Horizon Dynamical Prediction

This work introduces Learnable Lens Networks (LLN), a physics-inspired architecture that replaces direct feature-space residual accumulation with learnable optical transport in an augmented position-angle phase space and establishes that LLN transport is globally invertible and volume-preserving for any differentiable...

Bin-Bin Yong, Zhao Su, Lan Guo et al. · 0 citations
Preprint Aug 2026

HyperANFIS: Enhancing Rule Representation and Interpretability in Adaptive Neuro-Fuzzy Systems via Hyperbolic Geometry

Hyperbolic ANFIS (HyperANFIS), a hyperbolic extension of ANFIS that preserves the fuzzy semantics and core architecture of conventional ANFIS while performing rule-prototype learning, rule activation, and consequent aggregation in hyperbolic space, strengthens the fuzzy inference process.

Haoran Pei, Zhao Su, Ze-Tao Lin et al. · 0 citations

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