Papers arxiv:2605.13757 FrameSkip: Learning from Fewer but More Informative Frames in VLA Training Published on May 13 Submitted by yubin on May 14 Zhongguancun Academy Authors: Bin Yu , Shijie Lian , , , , , , , , , Abstract FrameSkip is a data-layer frame selection method that improves VLA policy… …
Papers arxiv:2605.01640 Prescriptive Scaling Laws for Data Constrained Training Published on May 2 Submitted by Justin Lovelace on May 8 Authors: , , , , Abstract A modified scaling law accounts for data repetition effects and provides compute-optimal training strategies for data-constrained scenar… …
… AI-generated summary Model internals encode rich information about how a large language model LLM processes its training data; however, post-training data engineering largely relies on external signals and ignores rich intrinsic signals lying in model internals. …
… AI-generated summary Pixel diffusion models have recently regained attention for visual generation. However, training advanced pixel-space models from scratch demands prohibitive computational and data resources. …
Papers arxiv:2604.28075 Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling Published on Apr 30 Submitted by Stefan Schweter on May 5 Boldt Authors: Ansar Aynetdinov , Patrick Haller , Abstract Training high-quality filtered data multiple times yields… …
… Despite rapid progress, top-tier multimodal search agents remain difficult to reproduce, largely due to the absence of open high-quality training data, transparent trajectory synthesis pipelines, or detailed training recipes. …
… AI-generated summary Clinical reasoning demands multi-step interactions -- gathering patient history, ordering tests, interpreting results, and making safe treatment decisions -- yet a unified training environment provides the breadth of clinical domains and specialized tools to train generalizable… …
Papers arxiv:2604.25441 Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost Published on Apr 28 Submitted by Venkata Pushpak Teja Menta on Apr 30 Praxel Authors: Venkata Pushpak Teja Menta Abstract Researchers e… …
… Moreover, FST-trained models remain closer to the base LLM up to 70% less KL divergence , resulting in less catastrophic forgetting than RL-training. …
… The business impact here is huge: instead of needing dedicated DevOps engineers to manage training pipelines, data scientists can now iterate much faster on custom models. …