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Retail search systems serve diverse geographic regions with distinct query patterns, vocabularies, and product prefer...
Diffusion TV is an interactive AI art installation that offers a tangible and embodied experience of diffusion models...
We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the d...
Group relative policy optimization for reinforcement learning with verifiable rewards (RLVR) typically uses a fixed i...
We study the problem of generating a compositional 3D representation of a cluttered scene containing hundreds of obje...
Layer dropout (a.k.a. stochastic depth) has been shown to enable faster training, higher accuracy, and robustness to ...
Quantization is widely used to reduce the computational and memory demands of neural-network inference. In recurrent ...
On-policy distillation (OPD) provides dense, per-token supervision for language model post-training, but its effectiv...
Designing and authoring high-performance custom kernels for accelerators is a complex task that requires deep hardwar...
Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful...
An avatar that holds a conversation should decide what to say and to move while saying it, yet these abilities live i...
Large language models (LLMs) are increasingly used to formulate optimization models from natural-language problem des...