3 accepted papers
Generative sequence modeling faces a fundamental tension between the expressivity of Transformers and the efficiency of linear sequence models. Existing efficient architectures are theoretically bounded by shallow, single-step linear updates, while powerful iterative methods like Test-Time Training …
Learning discriminative point-wise representations remains the central challenge in scene-level, correspondence-based point cloud registration. Most existing methods process two frames independently during the early stage and introduce cross-frame interaction only at coarsest stages. Such delayed in
Evolutionary algorithms (EAs) are widely used for multi-objective optimization due to their population-based nature. Traditional multi-objective EAs (MOEAs) generate a large set of solutions to approximate the Pareto front, leaving a decision maker (DM) with the task of selecting a preferred solutio…