Filtered to natural language processing · clear filter
This paper presents a system that can generate research papers end-to-end, from retrieving literature to producing publication-ready figures, and includes checks to ensure the accuracy and validity of the research. Practitioners might care about this system because it could streamline the process of writing research papers and reduce errors.
This paper introduces AuK, an open-source model for speech generation and editing, which can perform a range of tasks with a single interface and achieves state-of-the-art performance on several tasks. Practitioners may care about this model for its potential to improve speech synthesis and editing capabilities in applications such as voice assistants and audio editing software.
This paper explores how AI systems can improve themselves in a self-sustaining way, allowing them to adapt and learn from their experiences without human intervention. Practitioners might care about this research if they're looking for ways to create more autonomous and efficient AI systems.
This paper creates a system called ScienceIDE that converts scientific code into environments that can be used to train artificial agents to perform scientific tasks. Practitioners might care because this could lead to more efficient and effective ways to develop scientific intelligence.
This paper proposes a new method for training long-horizon search agents that can search, retrieve, and integrate evidence to reach a final answer. Practitioners in natural language processing and AI research might care about this paper because it shows a way to improve the performance of search agents, which can be used in applications such as question-answering systems.
This paper presents two search agents, Iris-mini and Iris-pro, trained to solve complex search tasks using reinforcement learning and self-supervised learning. Practitioners might care because these models achieve state-of-the-art results on various benchmarks, demonstrating the potential of AI-powered search agents in real-world applications.