…View arXiv page View PDF GitHub 66 Add to collection Community This is an automated message from the Librarian Bot . I found the following papers similar to this paper. The following papers…
…an upward distillation process, called Knowledge Seeding , where the memories of a smaller-self are distilled into a larger network to provide more capacity while preserving the knowledge. As a proof of…
…By representing spatial contact and constraint patterns as discrete tokens, the model captures complex structural interactions in a purely sequential manner, without relying on explicit coordinates or geometric neural networks. This unified…
…Code is available at https://github.com/Snowflake-AI-Research/ fastkernels View arXiv page View PDF Project page Add to collection Community FastKernels: A production-aligned GPU kernel generation benchmark that doubles…
…AI-generated summary Recent methods for arbitrary-skeleton motion capture from monocular video follow a factorized pipeline, where a Video-to-Pose network predicts joint positions and an analytical inverse-kinematics (IK…
…Integrated as a parallel branch alongside the Feed-Forward Network (FFN) in LVLMs, PVM establishes a distance-agnostic retrieval pathway that directly provides visual embeddings for precise visual perception , thereby structurally mitigating…
…With 7, 402 neural networks trained in total across 95 unique cross-domain tasks , MMDG-Bench yields five key findings: (1) under fair comparisons, recent specialized MMDG methods offer only marginal improvements…
…Using this simple strategy, we show that network training is significantly accelerated across diverse data modalities, including images and 3D structured shapes. Moreover, ComboStoc enables a new way of test time generation…
…ESamp is motivated by the well-known observation that neural networks tend to make lower-error predictions on inputs similar to those encountered before, and incur higher prediction error on novel ones…
…AutoEdit rewrites selected tokens using the same model, without requiring an auxiliary refinement network. To train this capability, we use a two-stage procedure. First, we construct structure-aware perturbations of expert…