5,762 results for aikatsu akari generation

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ViMax: Agentic Video Generation - GitHub

ViMax is a multi-agent video framework that enables automated multi-shot video generation while ensuring character and scene consistency. Our system seamlessly translates your ideas into …

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ViMax: Agentic Video Generation - GitHub

ViMax is a multi-agent video framework that enables automated multi-shot video generation while ensuring character and scene consistency. Our system seamlessly translates your ideas into …

en.wikipedia.org/wiki/IPad_Pro_%281st_generation%29

IPad Pro (1st generation) - Wikipedia

The first generation of iPad Pro is a line of iPad, a tablet computer developed and marketed by Apple. The iPad Pro was released in 2015 alongside the

www.reddit.com/r/CDrama/comments/1ripz05/generation_to_generation_whats_the_verdict_so_far/

Generation to generation - what's the verdict so far?

Seeing how many episodes of this drama are out now, but hesitating to watch due to how people talk about it - how does this drama compare to other adaptations of the author's works? I see some people...

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All the Generation Names and Years (1845 - 2039)!

Explore the names, years, defining events, and key behaviors of every generation since 1900 in this ultimate guide to generational history.

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A Year-by-Year Generation Guide and Their Personalities

Sep 26, 2025 · A generation is a group of people born at roughly the same time. They're usually grouped by a 20-year time interval, says Deborah Carr, PhD, professor and chair of the sociology …

arxiv.org/abs/2304.04746v1

A Cheaper and Better Diffusion Language Model with Soft-Masked Noise

Diffusion models that are based on iterative denoising have been recently proposed and leveraged in various generation tasks like image generation. Whereas, as a way inherently built for continuous data, existing diffusion models still have some limi...

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ViMax: Agentic Video Generation - GitHub

ViMax is a multi-agent video framework that enables automated multi-shot video generation while ensuring character and scene consistency. Our system seamlessly translates your ideas into …

arxiv.org/abs/1104.5620v3

The next-generation liquid-scintillator neutrino observatory LENA

We propose the liquid-scintillator detector LENA (Low Energy Neutrino Astronomy) as a next-generation neutrino observatory on the scale of 50 kt. The outstanding successes of the Borexino and KamLAND experiments demonstrate the large potential of liq...

arxiv.org/abs/2505.03763v1

Splitwiser: Efficient LM inference with constrained resources

Efficient inference of LLMs remains a crucial challenge, with two main phases: a compute-intensive prompt computation and a memory-intensive token generation. Despite existing batching and scheduling techniques, token generation phases fail to fully...

en.wikipedia.org/wiki/IPad_%286th_generation%29

IPad (6th generation) - Wikipedia

The sixth generation iPad (also referred to as the iPad 9.7-inch) is a tablet computer developed and marketed by Apple. It was announced and released in

en.wikipedia.org/wiki/IPad_%287th_generation%29

IPad (7th generation) - Wikipedia

The seventh-generation iPad (also referred to as the iPad 10.2-inch) is a tablet computer developed and marketed by Apple. It has a 10.2-inch (26 cm) Retina

arxiv.org/abs/1807.07281v3

ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech

In this work, we propose a new solution for parallel wave generation by WaveNet. In contrast to parallel WaveNet (van den Oord et al., 2018), we distill a Gaussian inverse autoregressive flow from the autoregressive WaveNet by minimizing a regularize...

arxiv.org/abs/1008.0063v1

Evolutionary Approach to Test Generation for Functional BIST

In the paper, an evolutionary approach to test generation for functional BIST is considered. The aim of the proposed scheme is to minimize the test data volume by allowing the device's microprogram to test its logic, providing an observation structur...

arxiv.org/abs/2206.09010v1

LIMO: Latent Inceptionism for Targeted Molecule Generation

Generation of drug-like molecules with high binding affinity to target proteins remains a difficult and resource-intensive task in drug discovery. Existing approaches primarily employ reinforcement learning, Markov sampling, or deep generative models...