www.bing.com/ck/a?!&&p=748bc0a9ee2b714316c68cf7316438a2eb3d47fc865eed3f58a3020a186dae75JmltdHM9MTc3MjU4MjQwMA&ptn=3&ver=2&hsh=4&fclid=31adac8f-e6cf-6fc7-2435-bb9de7766e52&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 …
arxiv.org/abs/2512.01896v1
Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises. While large language models have made automated report generation technically feasible, systematic research in this specific...
arxiv.org/abs/2407.01626v1
Existing KBQA methods have traditionally relied on multi-stage methodologies, involving tasks such as entity linking, subgraph retrieval and query structure generation. However, multi-stage approaches are dependent on the accuracy of preceding steps,...
arxiv.org/abs/2003.04874v3
We consider the problem of look-ahead economic dispatch (LAED) with uncertain renewable energy generation. The goal of this problem is to minimize the cost of conventional energy generation subject to uncertain operational constraints. The risk of vi...
arxiv.org/abs/2511.18281v1
Diffusion models (DMs) produce high-quality images, yet their sampling remains costly when adapted to new domains. Distilled DMs are faster but typically remain confined within their teacher's domain. Thus, fast and high-quality generation for novel...
arxiv.org/abs/2502.13081v1
Recent advancements in generative models have significantly facilitated the development of personalized content creation. Given a small set of images with user-specific concept, personalized image generation allows to create images that incorporate t...
arxiv.org/abs/2405.12978v1
We present personalized residuals and localized attention-guided sampling for efficient concept-driven generation using text-to-image diffusion models. Our method first represents concepts by freezing the weights of a pretrained text-conditioned diff...
www.bing.com/ck/a?!&&p=80c39415671d4e2cbec5dca1782bf036c671300124bbd998483a3cce9c8f1c78JmltdHM9MTc3MjU4MjQwMA&ptn=3&ver=2&hsh=4&fclid=2d90ddf4-e3a8-6a9b-176e-cae6e29e6b2c&u=a1aHR0cHM6Ly93d3cud2Vmb3J1bS5vcmcvc3Rvcmllcy8yMDI1LzA3L2NsaW1hdGUtcHJvb2ZpbmctYnVpbHQtZW52aXJvbm1lbnQtaW5mcmFzdHJ1Y3R1cmUtZnV0dXJlLw&ntb=1
Jul 22, 2025 · As the climate crisis deepens, climate proofing infrastructure is essential, not just for resilience, but also to ensure fairness for future generations.
arxiv.org/abs/hep-ph/9405313v2
We analyze some consequences of grand unification of the third-generation Yukawa couplings, in the context of the minimal supersymmetric standard model. We address two issues: the prediction of the top quark mass, and the generation of the top-bott...
arxiv.org/abs/2509.23825v1
We propose $\textbf{E}$lectric $\textbf{C}$urrent $\textbf{D}$iscrete $\textbf{D}$ata $\textbf{G}$eneration (ECD$^{2}$G), a pioneering method for data generation in discrete settings that is grounded in electrical engineering theory. Our approach dra...
arxiv.org/abs/2406.17777v1
Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising. One significant unresolved aspect within T2V is the effective visualization of text within generated videos. Despite the progress a...
arxiv.org/abs/2508.04943v1
Dynamic Scene Graph Generation (DSGG) aims to create a scene graph for each video frame by detecting objects and predicting their relationships. Weakly Supervised DSGG (WS-DSGG) reduces annotation workload by using an unlocalized scene graph from a s...
arxiv.org/abs/1908.09591v2
Our goal of patent claim generation is to realize "augmented inventing" for inventors by leveraging latest Deep Learning techniques. We envision the possibility of building an "auto-complete" function for inventors to conceive better inventions in th...
arxiv.org/abs/2411.00877v1
This paper addresses the problem of scheduling non-preemptive tasks with release jitter and execution time variation on a uniprocessor. We show that the schedulability analysis based on schedule graph generation, proposed by Nasri and Brandenburg [RT...
arxiv.org/abs/2407.17911v1
Diffusion models revolutionize image generation by leveraging natural language to guide the creation of multimedia content. Despite significant advancements in such generative models, challenges persist in depicting detailed human-object interactions...
arxiv.org/abs/2308.14217v1
Knowledge Graphs (KGs) have been used to support a wide range of applications, from web search to personal assistant. In this paper, we describe three generations of knowledge graphs: entity-based KGs, which have been supporting general search and qu...
arxiv.org/abs/2106.03337v1
Many conversation datasets have been constructed in the recent years using crowdsourcing. However, the data collection process can be time consuming and presents many challenges to ensure data quality. Since language generation has improved immensely...
arxiv.org/abs/1307.2993v1
One of the proposals for the exploitation of two-dimensional quantum walks has been the efficient generation of entanglement. Unfortunately, the technological effort required for the experimental realization of standard two-dimensional quantum walks...
arxiv.org/abs/1805.04833v1
We explore story generation: creative systems that can build coherent and fluent passages of text about a topic. We collect a large dataset of 300K human-written stories paired with writing prompts from an online forum. Our dataset enables hierarchic...
arxiv.org/abs/2112.07259v1
Long story generation (LSG) is one of the coveted goals in natural language processing. Different from most text generation tasks, LSG requires to output a long story of rich content based on a much shorter text input, and often suffers from informat...
