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FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets
FurE reconstructs realistic 3D animal fur from multi-view images using a novel strand-based method, achieving 10x speedup without animal-fur datasets.
Telescopic Language Models
Telescopic Language Models (TLMs) are single, nested Transformers that function as valid LMs at various capacities, trained with stochastic prefix supervision.
PDMD: Projected Distribution Matching Distillation for Video Diffusion Models
PDMD stabilizes video diffusion model distillation by projecting out critic errors, improving sample quality and efficiency with minimal code changes.
Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning
This paper introduces UMM-Reflection, an RL method for unified multimodal models to self-repair image generations through interleaved reflection and revision.
Retrieving Biblical Intertextual References in Karen Blixen's Seven Gothic Tales
This paper evaluates computational methods for retrieving biblical intertextual references in Karen Blixen's 'Seven Gothic Tales,' comparing sparse and dense models.
Reliability-Gated Fusion of Consumer Head and Foot IMUs for Lower-Body 3D Pose
This paper introduces a reliability-gated fusion model for consumer head and foot IMUs, improving 3D lower-body pose estimation by learning to trust sensor channels.
Unifying Distributional Training for One-Step Visual Generation
This paper unifies distributional training for one-step visual generation and introduces MGFlow, a new method achieving state-of-the-art results.
DexRoam: Learning Mobile Bimanual Dexterous Manipulation from Egocentric Whole-Body Human Demonstrations
DexRoam enables robots to learn complex mobile bimanual manipulation from egocentric human demonstrations, improving success rates and data efficiency.
TokenCast: Forecasting Token Consumption During LLM Agent Execution
TokenCast predicts LLM agent token consumption by learning composable cost representations, improving forecast accuracy and budget control.
Scaling Long-Form Story Generation via Narrative State Tracking
NstAgent is a training-free framework that enables LLMs to generate consistent, high-quality long-form stories up to 100K words by tracking narrative state.
Neural Harmonic Measure Operator
NHMO is a neural solver for elliptic PDEs on variable-shape domains, using a transformer-based boundary kernel for efficient solutions.
How to Loop MoE: Flatten the Experts, Untie the Attention
Foil introduces a novel method for looping Mixture-of-Experts (MoE) models, improving expert utilization and pretraining loss through flattened experts and untied attention.
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