…When to Pretrain with Your Finetuning Data (2026) Is More Data Worth the Cost? Dataset Scaling Laws in a Tiny Attention-Only Decoder (2026) Time is Not Compute: Scaling Laws for Wall…
…while preserving foundational knowledge and enabling constant-time inference through geometric constraints on adapter manifolds. AI-generated summary We address the challenge of knowledge composition in Vision-Language Models (VLMs), where accumulating…
…All shaping is training-only; inference cost is unchanged. On 170M-parameter language modeling , the shaped student at 8 steps achieves 32% lower perplexity than the 1,024-step teacher while being…
…From a single quadratic cost , joint minimization yields a unified solution that decomposes orthogonally into two distinct channels. The pace channel compresses execution along the planned direction, while the path channel applies…
…This suggests a scaling principle for distributed generative AI : predictable gains can be achieved by composing specialists, offering a complementary path toward AGI-level systems . View arXiv page View PDF Project page…
…Existing acceleration methods either require costly retraining with architectural changes or suffer from severe performance drop at high sparsity due to train-inference mismatch. To address these limitations, we propose BEAM (Binary…
…Training-free alternatives avoid such post-training, but often shift the cost to test-time optimization or extra denoising-time guidance. We propose Warp-as-History, a simple interface that turns camera…
…Together, the Darwin Family demonstrates that diagnostic-guided evolutionary merging is a practical and reproducible alternative to costly post-training pipelines for reasoning-centric language models. View arXiv page View PDF Project…
…Most existing methods remain tied to mesh connectivity and vertex-level message passing, which limits their applicability to mesh-free inputs such as point clouds and leads to high computational cost. Efficiently…
…mixed RLVR suffers from inter-capability divergence cost, while the pipeline of first training experts and then performing OPD , though avoiding divergence, fails to fully absorb teacher capabilities due to large behavioral…