Today's highest-signal AI research entities — latest papers with viability scores, trending topics, freshest articles, and the most popular FAQs — bundled into one quiet-canvas discovery hub.
An AI coding agent supervised by a physicist to build scientific software revealed limitations in architectural proposal and distinguishing predictive adequacy from explanatory correctness.
VideoMLA reduces KV cache memory in autoregressive video diffusion by 92.7% using a low-rank latent attention mechanism, improving throughput and matching quality at long horizons.
LLMSurgeon diagnoses the data mixture of large language models from generated text by framing it as an inverse problem, enabling post-hoc auditing of foundation models.
SchGen generates editable PCB schematics from natural language using a semantically grounded code representation, transforming hardware design into a task amenable to LLMs.
An efficient vision-language model for accurate and interpretable time-series anomaly detection, outperforming existing methods.
A novel latent reasoning method for LLMs that uses fixed memory blocks to unlock working memory for compute-efficient reasoning.
GPIC offers a comprehensive and large-scale image corpus for AI visual generation innovation.
A framework to quantify and repair compositional incoherence in multi-component LLM agents.