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Optimizing Prompts for Text-to-Image Generation Y aru Hao
Well-designed prompts can guide text-to-image models to generate amazing images.
CausalChaos for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes
Understanding the intricate motivations behind human actions is paramount in developing sophisticated systems capable of nuanced behavior analysis.
Collaborative Refining for Learning from Inaccurate Labels
For samples where some annotators disagree, a comparative strategy is proposed to filter noise.
StyleDrop: Text-to-Image Generation in Any Style Kihyuk Sohn Nataniel Ruiz Kimin Lee Daniel Castro Chin Irina Blok Huiwen Chang
Pre-trained large text-to-image models synthesize impressive images with an appropriate use of text prompts.
a8808b75b299d64a23255bc8d30fb786-Paper-Conference.pdf
Can a physicist make only a finite number of errors in the eternal quest to uncover the law of nature? This millennium-old philosophical problem, known as inductive inference, lies at the heart of epistemology.
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
Typically, deep RL algorithms learn a policy in an online trial-and-error fashion using millions to billions of data.
The Small English Town Swept Up in the Global AI Arms Race
The residents of Potters Bar are working to protect the "green belt" of farms, forests, and meadows that surround London from the endless demand for AI infrastructure. A short drive from London, the town of Potters Bar is separated from the village of South Mimms by 85 acres of rolling farmland segmented by a scribble of hedgerows. In one of the fields, a lone oak serves as a rest stop along a public footpath. Lately, the tree has become a site of protest, too. A poster tied to its trunk reads: "NO TO DATA CENTRE."