A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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Kaleido introduces a family of generative models for photorealistic, unified object- and scene-level neural rendering by treating 3D as a sequence-to-sequence problem.
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Florence-2 unifies diverse vision tasks under a single sequence-to-sequence model using prompt-based instructions and a massive multitask dataset.
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mBART pre-trains a multilingual sequence-to-sequence denoising auto-encoder on large-scale monolingual corpora using the BART objective, significantly improving machine translation.
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UniLM uses a shared Transformer with custom attention masks to unify bidirectional, unidirectional, and sequence-to-sequence pre-training for both NLU and NLG.