arxiv.org/abs/2510.17519v2
In recent years, large-scale generative models for visual content (\textit{e.g.,} images, videos, and 3D objects/scenes) have made remarkable progress. However, training large-scale video generation models remains particularly challenging and resourc...
arxiv.org/abs/2502.07701v3
In this technical report, we present Magic 1-For-1 (Magic141), an efficient video generation model with optimized memory consumption and inference latency. The key idea is simple: factorize the text-to-video generation task into two separate easier t...
arxiv.org/abs/2503.08638v2
We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the LLaMA2 architecture. Specifically, YuE scales to trillions of tokens a...
arxiv.org/abs/2407.17404v2
Game Description Language (GDL) provides a standardized way to express diverse games in a machine-readable format, enabling automated game simulation, and evaluation. While previous research has explored game description generation using search-based...
arxiv.org/abs/2412.00719v2
Talking head video generation aims to generate a realistic talking head video that preserves the person's identity from a source image and the motion from a driving video. Despite the promising progress made in the field, it remains a challenging and...
arxiv.org/abs/2506.19852v2
Recent advances in diffusion models have enabled high-quality video generation, but the additional temporal dimension significantly increases computational costs, making training and inference on long videos prohibitively expensive. In this paper, we...
arxiv.org/abs/2408.15474v1
Rap, a prominent genre of vocal performance, remains underexplored in vocal generation. General vocal synthesis depends on precise note and duration inputs, requiring users to have related musical knowledge, which limits flexibility. In contrast, rap...
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The fourth generation of Xbox models, simply named Xbox, [47] includes the Xbox Series X and Xbox Series S that launched on November 10, 2020. Both are considered members of the ninth generation …
arxiv.org/abs/2508.01696v3
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs), especially for knowledge-intensive tasks. Despite its advantages, current RAG methods often struggle to fully exploit knowledge during generation. In particular, the synergy...
arxiv.org/abs/2309.01948v1
In this study, we propose an automatic diary generation system that uses information from past joint experiences with the aim of increasing the favorability for robots through shared experiences between humans and robots. For the verbalization of the...
arxiv.org/abs/2511.00062v2
We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2World, Image2World, and Video2World generation in a single model and l...
arxiv.org/abs/2503.14492v2
We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmentation, depth, and edge. In the design, the spatial conditional scheme...
github.com/SebLague/Procedural-Cave-Generation
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arxiv.org/abs/2412.18708v1
We present Chunked Augmented Generation (CAG), an architecture specifically designed to overcome the context window limitations of Google Chrome's built-in Gemini Nano model. While Chrome's integration of Gemini Nano represents a significant advancem...
arxiv.org/abs/2501.02338v1
This bachelor's thesis examines the capabilities of ChatGPT 4 in code generation across 19 programming languages. The study analyzed solution rates across three difficulty levels, types of errors encountered, and code quality in terms of runtime and...
arxiv.org/abs/2403.17001v1
Recent innovations on text-to-3D generation have featured Score Distillation Sampling (SDS), which enables the zero-shot learning of implicit 3D models (NeRF) by directly distilling prior knowledge from 2D diffusion models. However, current SDS-based...
arxiv.org/abs/2508.11433v2
Multimodal Large Language Models (MLLMs) with unified architectures excel across a wide range of vision-language tasks, yet aligning them with personalized image generation remains a significant challenge. Existing methods for MLLMs are frequently su...
www.bing.com/ck/a?!&&p=ad610593c4b4aa6d8b421f035ad57ed7e91d10370ae94e6977abc87d81be6425JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=2a7bf399-dece-6a39-2759-e488dfe86bc6&u=a1aHR0cHM6Ly9kaWN0aW9uYXJ5LmNhbWJyaWRnZS5vcmcvZGljdGlvbmFyeS9lbmdsaXNoL2dlbmVyYXRpb24&ntb=1
GENERATION definition: 1. all the people of about the same age within a society or within a particular family: 2. a…. Learn more.
www.bing.com/ck/a?!&&p=908a0077d5b8296b1cab822734199dc64d263b85a36260d00a58ea1f081fc4fbJmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=2a7bf399-dece-6a39-2759-e488dfe86bc6&u=a1aHR0cHM6Ly93d3cudXNhdG9kYXkuY29tL3N0b3J5L2dyYXBoaWNzLzIwMjQvMTAvMDgvZ2VuZXJhdGlvbi1uYW1lcy15ZWFycy1leHBsYWluZWQvNzQ3MDE5NzQwMDcv&ntb=1
Oct 8, 2024 · Find your generation — and what it means — by your birth year. Where were you when the space shuttle Challenger exploded? The answer to that question is just one example of how …
www.bing.com/ck/a?!&&p=1017010e7f4c13ab2276afb3841b3627db3e9ae9fdb5df044e0ba2057feadd19JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=2a7bf399-dece-6a39-2759-e488dfe86bc6&u=a1aHR0cHM6Ly93d3cudG9kYXkuY29tL3BhcmVudHMvdGVlbnMvZ2VuZXJhdGlvbi1uYW1lcy1yY25hMTM3NDU3&ntb=1
Sep 26, 2025 · Here's how to define the different generation names. Gen Z was born between 1997 and 2012 and is considered the first generation to have largely grown up using the internet, modern …