Text-to-Video: a Two-stage Framework for Zero-shot Identity-agnostic Talking-head Generation

The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs).

We propose a data augmentation strategy, named DFM-X, that leverages knowledge about frequency shortcuts, encoded in Dominant Frequencies Maps computed for image classification models.

To overcome the above issues, we introduce CycleAdapt, which cyclically adapts two networks: a human mesh reconstruction network (HMRNet) and a human motion denoising network (MDNet), given a test video.

In this paper, we propose a novel task, Proactive News Grounded Conversation, in which a dialogue system can proactively lead the conversation based on some key topics of the news.

Modern deep neural networks, particularly recent large language models, come with massive model sizes that require significant computational and storage resources.

Efficiently Train Open-Source Language Models for Business