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Graphical Contrastive Losses for Scene Graph Parsing.

, , , , and . CVPR, page 11535-11543. Computer Vision Foundation / IEEE, (2019)

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cuDNN: Efficient Primitives for Deep Learning., , , , , , and . CoRR, (2014)Graphical Contrastive Losses for Scene Graph Generation., , , , and . CoRR, (2019)Mellotron: Multispeaker Expressive Voice Synthesis by Conditioning on Rhythm, Pitch and Global Style Tokens., , , and . ICASSP, page 6189-6193. IEEE, (2020)Panoptic-Based Image Synthesis., , , , and . CVPR, page 8067-8076. Computer Vision Foundation / IEEE, (2020)Evaluating Parameter Efficient Learning for Generation., , , , , , , , and . EMNLP, page 4824-4833. Association for Computational Linguistics, (2022)One TTS Alignment to Rule Them All., , , , , and . ICASSP, page 6092-6096. IEEE, (2022)Any-to-Any Voice Conversion with F0 and Timbre Disentanglement and Novel Timbre Conditioning., , , and . ICASSP, page 1-5. IEEE, (2023)Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning., , , , , , , , , and 6 other author(s). EMNLP (Findings), page 11844-11857. Association for Computational Linguistics, (2023)NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models., , , , , , and . CoRR, (2024)Persistent RNNs: Stashing Recurrent Weights On-Chip., , , , , , , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2024-2033. JMLR.org, (2016)