Search papers, labs, and topics across Lattice.
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DenseReward synthesizes diverse failure trajectories automatically, enabling robots to learn from a rich array of failure modes without human labeling.
HCC-STAR not only surpasses leading models in treatment accuracy but also offers a significant survival advantage, highlighting the potential of AI in precision oncology.
Even state-of-the-art language models struggle significantly in real-world tasks, exposing critical shortcomings in their deployment readiness.
Surpassing human performance in gaze estimation, PaGE closes the human-AI gap by over 60% while remaining lightweight for real-world applications.
Achieving multi-class segmentation and classification of intracranial aneurysms across diverse imaging modalities could revolutionize treatment planning and risk assessment.
Pretraining action modules with motion priors can drastically enhance VLA model performance, achieving faster convergence and better success rates in complex robot manipulation tasks.
VisualClaw slashes API costs by 98% while boosting accuracy, transforming how VLMs can operate in real-time environments.
Robots can now adjust their manipulation speed on-the-fly, achieving both rapid execution in low-risk phases and precision in high-risk tasks.
Stop stress-testing your autonomous vehicles in a vacuum: this closed-loop framework turns adversarial scenario generation into an adaptive curriculum that actually improves robustness.
Current AI agents struggle to maintain accurate beliefs in evolving information environments, with performance varying significantly based on both model capability (15.4% range) and framework design (9.2%).
Forget hyperparameter tuning – autonomous research reveals that bug fixes and architectural tweaks unlock far greater gains in multimodal agent memory.
LLM agents can now learn on the fly and adapt to evolving user needs without disruptive downtime, thanks to a novel meta-learning framework that synthesizes new skills from failure trajectories and optimizes the base policy during inactive periods.
