Search papers, labs, and topics across Lattice.
100 papers published across 8 labs.
Purely synthetic training data outperforms native real-world supervision on satellite stereo benchmarks, showing that pristine geometric labels and zero temporal noise beat noisy real-world data collection.
Purely synthetic training data outperforms native real-world supervision on satellite stereo benchmarks, showing that pristine geometric labels and zero temporal noise beat noisy real-world data collection.
Non-linear electrochemical transport equations can now be solved on noisy quantum hardware, unlocking the first end-to-end quantum simulation of an entire battery cell.
Electrochemical and catalytic interfaces have long been an unaddressed blind spot for atomistic ML; 15.4 million ab initio configurations now supply the training scale required to model them accurately.
Fysiverse-3D-Vision is proposed, a unified vision-language-geometry framework for generative 3D scene reconstruction and executable asset construction from a single image that establishes a shared representation where spatial reasoning and geometric reconstruction mutually enhance each other, allowing object layouts to be inferred beyond the constraints of individual asset generators.
COPA is a robust active-perception framework for global-state-free aerial-ground cooperation that derives an active-perception model that relates UAV motion, gimbal angle, and UGV motion to the target image-plane state and uses these predictions to jointly optimize UAV and gimbal control.
This work presents and tackles two problems associated with deploying Foundation Models (FMs) on Embodied Agents performing navigation: Training bias in FMs leading to poor personalization in unseen environments, and Limited FM context length hindering success, especially on long horizon tasks.
A skill sequence planning method that enables a heterogeneous team of multi-functional robots to collaboratively perform construction assembly work using reusable, preprogrammed skills such as grasping, drilling, and fastening.
A simulator in which tissue is reconstructed from a fixed-view RGB-D recording of the surgical field, composited to remove the instruments, closed into watertight volumes and tetrahedralised, intended for closed-loop feasibility, safety, contact and policy screening.
CableVLA is presented, an end-to-end multimodal vision-language-action framework that converts simulation-privileged supervision into deployable cable-topology and tactile representations and cross-simulator and real-robot comparisons further examine zero-shot policy transfer under changes in dynamics and sensing.
An integrated robotics course framework that organizes these activities around a shared robotic artifact, and offers a structured approach for adapting robotics research workflows into interdisciplinary precollege courses.
Counterfactual Tucker Diffusion (CFTDiff), which integrates the treatment mask and latent Tucker structure into conditional diffusion to recover this distribution given observed control outcomes through efficient nonlinear score learning in a low-dimensional core, and establishes high-probability error bounds.
The MaP is proposed, a unified framework that seamlessly harmonizes divergent GUI navigation tasks and effectively mitigates gradient conflicts and significantly outperforms the direct mixture training, establishing a robust paradigm for multi-task GUI navigation.
This work proposes online conformal state probing (OCSP), an action and probing policy that certifies worst-case reliability levels without relying on distributional assumptions, and can be applied to existing pre-trained value-based control policies without requiring retraining or fine-tuning.
This paper proposes NeSyAM, a novel neurosymbolic modeling paradigm for action model learning under partial observability, and presents a unified variational framework for theoretically analysing the limitations of existing methods compared to this proposed approach.
GameDirector is introduced, the first agentic framework that decouples rule-based gameplay logic from visual rendering, allowing players to configure characters, states, and rules much like a game developer while preserving coherent game mechanics.
