Protein folding models share a two-stage trunk mechanism initializing biochemical signals then spatial features, with causally steerable, interchangeable representations across architectures.
Swift Sampling uses Taylor-series projections of visual feature trajectories to select temporally surprising frames, cutting overhead by 30x while boosting long-video accuracy up to 12.5 points.
Economic model combining scaling laws with microeconomics shows profit-optimal LLM training scales near-linearly with hardware efficiency and sub-quadratically in cost, while current expenditure trends are only optimal under compute-bound assumptions.
Regularized Newton training of overparameterized neural networks converges to a deterministic NNTK limit with exponentially fast uniform convergence across all frequencies, avoiding gradient descent's spectral bias.
A unified framework bounds DP privacy leakage against multi-target membership, attribute, and reconstruction attacks using only privacy parameters and adversarial baseline success rates.
GenScale benchmarks relative object scale in image generation and editing, finding current models unreliable, while Rescale improves scale plausibility via localized correction.
Activation patching's natural indirect effect embeds hidden interaction effects between components, which cause conditional importance to be invisible or inflated, explain faithfulness instability, scale with activation distance, and diagnose when greedy component ranking misses combinatorial mechan
PAIR reframes diffusion model concept erasure via unsafe-safe pairs, using paired semantic realignment and directional Fisher-weighted adaptation to remove targeted concepts while preserving structural and semantic consistency.
ReToken introduces one learnable retrieval token that selects sparse visual tokens from long contexts, improving vision-language models by up to 13.4 points on visual retrieval while fitting on a single GPU.
ACC++ improves circuit tracing to extract interpretable prompt-specific language model circuits from single passes, revealing clustered indirect-object mechanisms and language-specific reused components.