Posters

MVSDet uses efficient plane sweeps for accurate indoor 3D object detection from multiple images, significantly outperforming previous NeRF-based methods.

MVInpainter: Pose-free multi-view consistent inpainting bridges 2D and 3D editing by simplifying 3D editing to a multi-view 2D inpainting task.

MVGamba: A unified, feed-forward 3D content generation model achieving state-of-the-art quality and speed using an RNN-like state space model for efficient multi-view Gaussian reconstruction.

MV2Cyl: A novel method reconstructs 3D extrusion cylinder CAD models directly from multi-view images, surpassing accuracy of methods using raw 3D geometry.

MUVERA: Revolutionizing multi-vector retrieval with single-vector speed and accuracy!

Researchers introduce a novel approach to mutual information (MI) estimation using normalizing flows, providing accurate estimates even in high dimensions.

f-DIME: a novel class of discriminative mutual information estimators using f-divergence outperforms state-of-the-art methods by achieving an excellent bias-variance trade-off. This is achieved throug…

New algorithms conquer regret in multi-armed bandits challenged by network interference, achieving provably low regret with both known and unknown network structures.

MutaPLM: a novel protein language model, provides human-understandable mutation explanations and designs novel mutations with desirable properties using a unique protein delta network and chain-of-tho…

AI models struggle to understand 3D space like humans do. This paper introduces Multiview Scene Graphs (MSGs) – a new topological scene representation using interconnected place and object nodes buil…

This paper introduces an efficient multivariate stochastic dominance test using optimal transport, enabling robust model benchmarking by considering metric dependencies.

Boost multivariate time series forecasting accuracy by efficiently learning the complex correlation structure of prediction errors, enhancing reliability without expanding model size.

New method distills slow diffusion models into fast, few-step models by matching data expectations, achieving state-of-the-art results on ImageNet.

MultiPull: a novel method reconstructing detailed 3D surfaces from raw point clouds using multi-step optimization of multi-level features, significantly improving accuracy and detail.

Multiple Physics Pretraining (MPP) revolutionizes spatiotemporal physical surrogate modeling by pretraining transformers on diverse physics simultaneously, enabling accurate predictions on unseen syst…

Large Multimodal Models (LMMs) are limited by their context length during many-shot in-context learning. This paper introduces Multimodal Task Vectors (MTV), a method to compress numerous in-context …

AI-generated preference data improves text-to-image alignment.

Multilinear Mixture of Experts (μMoE) achieves scalable expert specialization in deep neural networks through tensor factorization, enabling efficient fine-tuning and interpretable model editing.

Multidimensional Fractional Programming (MFP) efficiently solves the challenging Normalized Cut (NCut) problem for multi-class clustering, outperforming existing methods.

This paper introduces a novel model for multi-winner reconfiguration, analyzing the computational complexity of transitioning between committees using four approval-based voting rules, demonstrating b…