Search papers, labs, and topics across Lattice.
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Selective visual-text compression in SEER boosts extraction precision while slashing token usage, outperforming leading models in long-context reasoning tasks.
Expanding cognitive capabilities in agentic AI systems could jeopardize human autonomy and control, necessitating urgent risk mitigation strategies.
ForgeWM achieves unmatched action-sign accuracy and motion-profile alignment in few-step video generation, outperforming existing models while reducing latency.
DURA reveals that visually indistinguishable adversarial patches can exploit VLA models, posing a significant threat to their deployment in real-world robotics.
LLMs can be fine-tuned to exhibit specific behavioral styles, revealing that personality-like traits are not just abstract concepts but measurable and controllable modes of interaction.
No single model-harness combination consistently outperforms others, highlighting the critical need for tailored evaluations in agent deployment.
On-policy distillation can lead to catastrophic length inflation in student models, but a simple fix stabilizes training and boosts performance by 7%.
