Storm
PulseAugur coverage of Storm — every cluster mentioning Storm across labs, papers, and developer communities, ranked by signal.
- 2026-05-19 research_milestone Researchers introduced STORM, a new system for multi-agent collaboration on shared codebases. source
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Obsession Star Inde Navarrette Meets MCU X-Men Director
The breakout star of the profitable horror film "Obsession," Inde Navarrette, has met with Jake Schreier, the director tapped to helm Marvel's upcoming "X-Men" movie. Navarrette's performance in "Obsession," which gross…
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New STORM framework enhances Mamba models by preserving spatial structure during token reduction
Researchers have developed STORM, a novel spatial-aware token reduction framework designed to address performance degradation in visual state space models like Mamba when subjected to token compression. Existing reducti…
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New research explores advanced sampling techniques for machine learning
Two new research papers explore advanced techniques for sampling from complex probability distributions, a critical task in machine learning. The first paper, submitted to arXiv, focuses on variance reduction methods li…
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STORM framework enhances lexical query expansion for retrieval
Researchers have developed STORM, a self-supervised framework for lexical query expansion that improves information retrieval. This method uses a reward-guided beam search to optimize token generation, making it more ef…
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STORM system improves multi-agent code collaboration with state management
Researchers have introduced STORM, a novel state-oriented management system designed to enhance collaboration among multiple AI agents working on shared codebases. Unlike existing methods that rely on workspace isolatio…
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New architectures enable real-time video understanding
Researchers are developing new methods for real-time video understanding, moving beyond traditional offline analysis. Several papers propose architectures that decouple visual perception from language generation to impr…
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Actor-Critic RL algorithms achieve optimal sample complexity for MDPs
Two new arXiv papers explore advancements in actor-critic reinforcement learning algorithms. The first paper, though later withdrawn, proposed an optimal sample complexity of O(ε−2) for single-timescale actor-critic met…