Graph diffusion models achieve state-of-the-art performance in graph generation but suffer from quadratic complexity in the number of nodes -- and much of their capacity is wasted modeling the absence of edges in sparse graphs. Inspired by latent diffusion in other modalities, a natural idea is to compress graphs into a low-dimensional latent space and perform diffusion in that space. However, unl
We introduce EPAG, a benchmark dataset and framework designed for Evaluating the Pre-consultation Ability of LLMs using diagnostic Guidelines. LLMs are evaluated directly through HPI-diagnostic guideline comparison and indirectly through disease diagnosis. In our experiments, we observe that small open-source models fine-tuned with a well-curated, task-specific dataset can outperform frontier LLMs
Today's inference-time workloads increasingly depend on timely access to a model's internal states. We present DMI-Lib, a high-speed deep model inspector that treats internal observability as a first-class systems primitive, decoupling it from the inference hot path via an asynchronous observability substrate built from Ring^2, a GPU-CPU memory abstraction for capturing and staging tensors, and a
Explainable artificial intelligence has emerged as a promising field of research to address reliability concerns in artificial intelligence. Despite significant progress in explainable artificial intelligence, few methods provide a systematic way to visualize and understand how classes are confused and how their relationships evolve as training progresses. In this work, we present GRAPHIC, an arch
Floating-point neural networks dominate modern machine learning but incur substantial inference costs, motivating emerging interest in Boolean networks for resource-constrained deployments. Since Boolean networks use only Boolean operations, they can achieve nanosecond-scale inference latency. However, learning Boolean networks that are both compact and accurate remains challenging because of thei
Capital is concentrating at the top of the market, with one dominant AI check dwarfing the rest of the cycle and adjacent flows still landing in grants and other large allocations.
Capital is concentrating at the top of the market, with one dominant AI check dwarfing the rest of the cycle and adjacent flows still landing in grants and other large allocations.
Capital is concentrating at the top of the market, with one dominant AI check dwarfing the rest of the cycle and adjacent flows still landing in grants and other large allocations.
Benchmark activity is narrow but clear: one system appears across multiple GAIA tiers, making the desk about breadth of coverage rather than a crowded leaderboard shift.
Benchmark activity is narrow but clear: one system appears across multiple GAIA tiers, making the desk about breadth of coverage rather than a crowded leaderboard shift.
Benchmark activity is narrow but clear: one system appears across multiple GAIA tiers, making the desk about breadth of coverage rather than a crowded leaderboard shift.