8 papers
From News to Returns: A Granger-Causal Hypergraph Transformer on the Sphere
Anoushka Harit, Zhongtian Sun, Jongmin Yu
We propose the Causal Sphere Hypergraph Transformer (CSHT), a novel architecture for interpretable financial time-series forecasting that unifies \emph{Granger-causal hypergraph st…
Quantifying Semantic Shift in Financial NLP: Robust Metrics for Market Prediction Stability
Zhongtian Sun, Chenghao Xiao, Anoushka Harit +1
Financial news is essential for accurate market prediction, but evolving narratives across macroeconomic regimes introduce semantic and causal drift that weaken model reliability.…
GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning
Zhongtian Sun, Anoushka Harit, Alexandra Cristea +2
Graph Neural Networks (GNNs) have demonstrated significant success in learning from graph-structured data but often struggle on heterophilous graphs, where connected nodes differ i…
EWC-Guided Diffusion Replay for Exemplar-Free Continual Learning in Medical Imaging
Anoushka Harit, William Prew, Zhongtian Sun +1
Medical imaging foundation models must adapt over time, yet full retraining is often blocked by privacy constraints and cost. We present a continual learning framework that avoids…
RicciFlowRec: A Geometric Root Cause Recommender Using Ricci Curvature on Financial Graphs
Zhongtian Sun, Anoushka Harit
We propose RicciFlowRec, a geometric recommendation framework that performs root cause attribution via Ricci curvature and flow on dynamic financial graphs. By modelling evolving i…
ManifoldMind: Dynamic Hyperbolic Reasoning for Trustworthy Recommendations
Anoushka Harit, Zhongtian Sun, Suncica Hadzidedic
We introduce ManifoldMind, a probabilistic geometric recommender system for exploratory reasoning over semantic hierarchies in hyperbolic space. Unlike prior methods with fixed cur…