Our study of 22 mitigation techniques and five baselines reveals up to 12.6% fairness variance across identical training runs with identical seeds.

Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using textdescriptions orreference images, while preserving irrelevant attributes(e.g.,identity,background,cloth).

The rise of large language models (LLMs) has significantly transformed both the construction and application of information retrieval (IR) systems. However, current interactions between IR systems and LLMs remain limited, with LLMs merely serving as part of components within IR systems, and IR systems being constructed independently of LLMs. This separated architecture restricts knowledge sharing and deep collaboration between them. In this paper, we introduce Self-Retrieval, a novel end-to-end LLM-driven information retrieval architecture.

The company launched its Sora 2 model in September 2025 alongside a dedicated Sora app. OpenAI plans to add its Sora video generation model directly into ChatGPT, reports . The standalone Sora app was seen as a smash hit when it launched alongside Sora 2 in September 2025, but interest in the video generation app has fallen in the time since as users ran into limits on the amount and kinds of videos they could create. Adding Sora to the ChatGPT could give the model a second life, and ideally grow the ChatGPT app's weekly active users from the 900 million OpenAI reported in February, to a billion or more. According to, the standalone Sora app will stick around after the model is integrated, even though the app has fallen out of the App Store's top 100 free apps and only a small number of users reportedly share their videos publicly in the app.

We propose stochastic ensemble value expansion (STEVE), a novel model-based technique that addresses this issue. By dynamically interpolating between model rollouts of various horizon lengths for each individual example, STEVE ensures that the model is only utilized when doing so does not introduce significant errors.