AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 5 of 25 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Gander is presented, a native multimodal duplex interaction model that builds on MiniCPM-o 4.5 and is further adapted for realtime interaction with an asynchronous agent loop and is released together with its models, code, and data to facilitate further research and development in the community.
Symbolic models make melody, harmony, rhythm, and form explicit but typically stop before a finished recording; audio models produce complete songs while leaving composition implicit. We introduce YuE2, which unifies symbolic and audio music generation at frontier quality through symbolic planning. A single AR-NAR Mixt...
MUUNRiver-Bench is presented, a diagnostic benchmark whose reference-audio queries use natural-language instructions to define relevance, and task-wise rank reversals reveal complementary biases: acoustic encoders favour local identity, whereas text-aligned encoders favour semantic relations.
This work introduces TUTTI (Transformer for Unified audio-To-score Transcription trained on Synthetic multi-Instrumentation Data), a pre-training paradigm driven by a purely synthetic, large-scale dataset that shows remarkable cross-instrument transferability, effectively adapting to unseen instruments with highly comp...
Experimental results indicate that fully automated data curation combined with imbalance-aware training yields non-trivial improvements, but models still struggle to capture fine-grained acoustic features, indicating a gap between surface-level alignment and deep musical comprehension.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.