controlled experiments
Controlled experiments in AI involve systematic testing where variables are manipulated in a controlled manner to evaluate their effects on model performance. These experiments help ensure reliable results and insights regarding model behavior and optimization strategies.
- Asymmetric REINFORCE for off-Policy Reinforcement Learning: Balancing positive and negative rewards
- Quantifying Cross-Modality Memorization in Vision-Language Models
- Quantifying Generalisation in Imitation Learning
- Split Gibbs Discrete Diffusion Posterior Sampling
- Through the Lens: Benchmarking Deepfake Detectors Against Moiré-Induced Distortions
- Understanding and Mitigating Numerical Sources of Nondeterminism in LLM Inference
- Understanding and Mitigating Numerical Sources of Nondeterminism in LLM Inference
- VLA-OS: Structuring and Dissecting Planning Representations and Paradigms in Vision-Language-Action Models