9 papers
CAGE: Certified Authorization under Typed-Return Uncertainty for Tool-Using Agents
Blaise Delattre, Cong Wang, Yang Cao
Tool-using LLM agents act on typed tool returns, records pairing provenance and categorical fields with numerical values. Runtime permission gates generally authorize the observed…
Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing
Erwan Fagnou, Paul Caillon, Blaise Delattre +1
Token mixing layers play a key role in how language models can learn and generate long-range dependencies. Their efficiency relies on the necessary trade-off between decoding speed…
Certified Robustness under Heterogeneous Perturbations via Hybrid Randomized Smoothing
Blaise Delattre, Hengyu Wu, Paul Caillon +2
Randomized smoothing provides strong, model-agnostic robustness certificates, but existing guarantees are limited to single modalities, treating continuous and discrete inputs in i…
Forward Only Learning for Orthogonal Neural Networks of any Depth
Paul Caillon, Alex Colagrande, Erwan Fagnou +2
Backpropagation is still the de facto algorithm used today to train neural networks. With the exponential growth of recent architectures, the computational cost of this algorithm a…
On the Stability of Neural Networks in Deep Learning
Blaise Delattre
Deep learning has achieved remarkable success across a wide range of tasks, but its models often suffer from instability and vulnerability: small changes to the input may drastical…
Conditional Distribution Quantization in Machine Learning
Blaise Delattre, Sylvain Delattre, Alexandre Vérine +1
Conditional expectation \mathbb{E}(Y \mid X) often fails to capture the complexity of multimodal conditional distributions \mathcal{L}(Y \mid X). To address this, we propose using…