# Zero-shot Learning

Level-Navi Agent is an open-source general-purpose web search agent framework that can decompose complex problems and progressively search for information on the internet until it answers user questions. By providing the Web24 dataset, covering five major fields: finance, games, sports, movies, and events, it provides a benchmark for evaluating model performance on search tasks. The framework supports zero-shot and few-shot learning, providing an important reference for the application of large language models in the field of Chinese web search agents.

Meta Motivo, released by Meta FAIR, is the first behavior-based model that leverages a novel unsupervised reinforcement learning algorithm for pre-training, designed to control complex virtual humanoid agents in completing full-body tasks. The model can tackle unseen tasks during testing, such as motion tracking, pose reaching, and reward optimization, without requiring additional learning or fine-tuning. The significance of this technology lies in its zero-shot learning ability, capable of managing a variety of complex tasks while maintaining behavioral robustness. The development of Meta Motivo stems from a pursuit of generalization capabilities for more complex tasks and different types of agents. Its open-source pre-trained models and training code encourage the community to further advance research on behavior-based models.

Diffusion Self-Distillation is a self-distillation technique based on diffusion models for zero-shot custom image generation. This technology allows artists and users to generate their own datasets via a pre-trained text-to-image model without requiring large paired datasets, enabling them to fine-tune the model for image-to-image tasks conditioned on text and images. This approach surpasses existing zero-shot methods in maintaining performance on identity generation tasks and can rival instance-based tuning techniques without the need for optimization during testing.

Voicv is a cutting-edge voice cloning platform that can transform your voice into digital assets in just minutes, supporting multiple languages and zero-shot learning. The platform combines advanced AI technology with user-friendly design, offering professional-grade voice cloning capabilities. Key advantages of Voicv include zero-shot voice cloning, multi-language support, real-time processing, high accuracy, cross-platform support, and enterprise readiness. Background information shows that Voicv is dedicated to assisting content creators, voice actors, and other users in producing multilingual content while maintaining their personal brand and vocal characteristics.

Omni-Zero-Couples is a zero-shot stylized couple portrait model utilizing the diffusers pipeline. It leverages deep learning technology to generate couple portraits in a specific artistic style without the need for predefined style samples. This technology has broad application prospects in the fields of artistic creation, personalized gift-making, and digital entertainment.

seed-vc is a voice conversion model based on the SEED-TTS architecture, capable of zero-shot voice conversion, meaning it can convert voices without requiring specific voice samples from individuals. This technology excels in audio quality and tonal similarity, holding substantial research and application value.

OpenVoice is an open-source voice cloning technology capable of accurately replicating reference voicemails and generating voices in various languages and accents. It offers flexible control over voice characteristics such as emotion, accent, and can adjust rhythm, pauses, and intonation. It achieves zero-shot cross-lingual voice cloning, meaning it does not require the language of the generated or reference voice to be present in the training data.