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Text world models can transform LLM-based agents from reactive responders into proactive planners, enhancing their performance in complex interactive tasks.
LVLMs can now perform visual search far more effectively thanks to a clever decoding strategy that harmonizes pre- and post-training capabilities.
Ditch the rigid grid: SP-MoMamba uses superpixels to let Mamba-based super-resolution models "see" images like humans do, boosting performance and efficiency.
Training VLMs on collaboratively generated Murder Mystery scripts dramatically improves their ability to reason about hidden facts and deception in complex, multi-agent scenarios.
