Abstract: The problem of learning a channel decoder is considered for two channel models. The first model is an additive noise channel whose noise distribution is unknown and nonparametric. The ...
Abstract: Multi-task dense scene understanding, which trains a model for multiple dense prediction tasks, has a wide range of application scenarios. Capturing long-range dependency and enhancing cross ...
Read full article about: Zuckerberg's plan to sell excess AI compute could finds its first big customer in Anthropic Meta is reportedly in talks with Anthropic to rent out compute capacity from its ...
Kimi is launching K3, a multimodal open-weight model with 2.8 trillion parameters and one million tokens of context. In the company’s own benchmarks, it comes close to Claude Fable 5 and GPT 5.6 Sol ...
This design is mostly based on the source code from https://github.com/russdill/bch_verilog. According to my requirements, the source code was packaged as "bch_enc ...
In this work, we introduce DINOv, a Visual In-Context Prompting framework for referring and generic segmentation tasks. For visualization and demos, we also recommend trying T-Rex demo link, which is ...
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