Pretraining on 1M wild videos followed by post-training on curated data yields high-fidelity feedforward 3D avatars that generalize across identities, clothing, and lighting with emergent relightability and loose-garment support.
Lan- guage models are few-shot learners.Advances in neural in- formation processing systems, 33:1877–1901
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STAC compresses KV caches in streaming 3D reconstruction transformers via temporal token preservation with decayed attention, spatial voxel compression, and chunked multi-frame optimization, delivering 10x memory reduction and 4x faster inference at SOTA quality.
3DrawAgent lets LLMs create complex 3D sketches from text prompts by using pairwise comparisons of their own outputs to self-improve spatial drawing skills without parameter updates.
RAD-2 uses a diffusion generator and RL discriminator to cut collision rates by 56% in closed-loop autonomous driving planning.
CG-CLIP adds caption-guided memory refinement and token-based spatiotemporal aggregation to CLIP for video person ReID, outperforming SOTA on MARS, iLIDS-VID, SportsVReID and DanceVReID.
An MLLM interpreter generates concise CDL descriptions from diagrams, enabling an off-the-shelf LLM to solve plane geometry problems competitively after training on only 5.5k examples.
citing papers explorer
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Large-scale Codec Avatars: The Unreasonable Effectiveness of Large-scale Avatar Pretraining
Pretraining on 1M wild videos followed by post-training on curated data yields high-fidelity feedforward 3D avatars that generalize across identities, clothing, and lighting with emergent relightability and loose-garment support.
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STAC: Plug-and-Play Spatio-Temporal Aware Cache Compression for Streaming 3D Reconstruction
STAC compresses KV caches in streaming 3D reconstruction transformers via temporal token preservation with decayed attention, spatial voxel compression, and chunked multi-frame optimization, delivering 10x memory reduction and 4x faster inference at SOTA quality.
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3DrawAgent: Teaching LLM to Draw in 3D with Early Contrastive Experience
3DrawAgent lets LLMs create complex 3D sketches from text prompts by using pairwise comparisons of their own outputs to self-improve spatial drawing skills without parameter updates.
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RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework
RAD-2 uses a diffusion generator and RL discriminator to cut collision rates by 56% in closed-loop autonomous driving planning.
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Beyond Pedestrians: Caption-Guided CLIP Framework for High-Difficulty Video-based Person Re-Identification
CG-CLIP adds caption-guided memory refinement and token-based spatiotemporal aggregation to CLIP for video person ReID, outperforming SOTA on MARS, iLIDS-VID, SportsVReID and DanceVReID.
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Concise Geometric Description as a Bridge: Unleashing the Potential of LLM for Plane Geometry Problem Solving
An MLLM interpreter generates concise CDL descriptions from diagrams, enabling an off-the-shelf LLM to solve plane geometry problems competitively after training on only 5.5k examples.