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From the 2 of 16 linked papers with an AI index.

collaborators

16 papers

cs.GT2026

DNQ: Deep Nash Q-Network for Partially Observable n-Player Games

Qintong Xie, Edward Koh, Xavier Cadet +1

The paper introduces DNQ, a deep reinforcement learning framework that trains bidding agents for partially observable n‑player games by alternating between trajectory collection, c…

cs.LG2026

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations

Chon-Fai Kam, Xavier Cadet, Miloud Bessafi +1

The paper analyzes two‑layer neural networks with holomorphic monomial activations (σ(z)=z^k) on modular arithmetic tasks, providing an exact algebraic condition for when a target…

cs.LG2026

RADAR: Relative Angular Divergence Across Representations

Xavier Cadet, Mateusz Nowak, Peter Chin

Machine learning methods rely on data. However, gathering suitable data can be challenging due to availability constraints, cost, or the need for domain expertise. Expanding datase…

quant-ph2026

Wavelet Variance Equipartition as a Threshold for World-Model Quality and Quantum Kernel TN-Simulability

Chon-Fai Kam, Xavier Cadet, Miloud Bessafi +1

While world models learn compact representations of complex environments, they lack a physics-grounded metric to assess the structural fidelity of their latent spaces. We identify…

cs.CR2026

Retrieval-Augmented LLMs for Security Incident Analysis

Xavier Cadet, Aditya Vikram Singh, Harsh Mamania +6

Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts, network traffic records, and authe…

quant-ph2026

Hermitian Matrix Function Synthesis without Block-Encoding

Anuradha Mahasinghe, Kaushika De Silva, Xavier Cadet +3

Implementing polynomial functions of Hermitian matrices on quantum hardware is a foundational task in quantum computing, critical for accurate Hamiltonian simulation, quantum linea…