FPILOT optimizes pre-trained RL trading policies at inference time using forecasted price trajectories to improve portfolio allocations and risk-adjusted returns on the DJ30 benchmark.
Certified robustness of graph neural networks against adversarial structural perturbation
3 Pith papers cite this work. Polarity classification is still indexing.
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PRAETORIAN reduces GNN backdoor attack success rate to 0.55% with 0.62% clean accuracy drop by targeting the need for many or highly influential trigger nodes.
CureLLM adds curvature-aware edge modeling and prompt-based alignment to graph LLMs, claiming to resolve over-squashing from negative curvature and outperforming 20 baselines on 11 datasets.
citing papers explorer
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Plan Before You Trade: Inference-Time Optimization for RL Trading Agents
FPILOT optimizes pre-trained RL trading policies at inference time using forecasted price trajectories to improve portfolio allocations and risk-adjusted returns on the DJ30 benchmark.
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Trapping Attacker in Dilemma: Examining Internal Correlations and External Influences of Trigger for Defending GNN Backdoors
PRAETORIAN reduces GNN backdoor attack success rate to 0.55% with 0.62% clean accuracy drop by targeting the need for many or highly influential trigger nodes.
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Edge-Aware Curvature Modeling for Graph Understanding in Large Language Models
CureLLM adds curvature-aware edge modeling and prompt-based alignment to graph LLMs, claiming to resolve over-squashing from negative curvature and outperforming 20 baselines on 11 datasets.