ClothTransformer is a unified latent-space Transformer for cloth simulation that handles body-driven garments, robotic manipulation, and free-fall collisions in one model with 4-9x lower error than prior methods and mesh-resolution independence.
SENC: handling self-collision in neural cloth simulation
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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Divergence Decoding steers LLM logits using small auxiliary models to unlearn specific data at inference time, outperforming baselines and generalizing to images.
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Divergence Decoding: Inference-Time Unlearning via Auxiliary Models
Divergence Decoding steers LLM logits using small auxiliary models to unlearn specific data at inference time, outperforming baselines and generalizing to images.