arXiv AI
LabInstruct: Benchmarking Situated Instructional Video Generation for Lab Procedures
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arXiv AI
Jun 12
LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories
arXiv:2606. 13578v1 Announce Type: cross Abstract: Scientific laboratories increasingly rely on AI systems to reason about experiments, but the physical act of doing science remains largely outside their reach.
arXiv Computer Vision
Oct 2
Ego2Act: Evaluating Goal-Directed Manipulation in Egocentric Video Generation
Ego2Act is a new benchmark that tests video generation models on goal‑directed, egocentric manipulation tasks. It contains 2,640 videos from 110 real‑world tasks, each requiring multiple steps of object manipulation to achieve a high‑level goal. The benchmark includes Ego2ActJudge, a reference‑free evaluation pipeline that better aligns with human judgments of task completion and physics plausibility.
arXiv AI
Jun 12
An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics
arXiv:2606. 12936v1 Announce Type: cross Abstract: Wet-lab robots can improve the reproducibility, throughput, and safety of biomedical experiments, but scaling their learning requires customizable simulators for safe and reproducible task generation, open editable laboratory assets, and efficient pipelines that turn limited demonstrations into usable training data.
arXiv AI
1d ago
BEAKER: An Expert-Curated Benchmark for Embodied Brains in Self-Driving Chemical Laboratories
BEAKER is a new benchmark for evaluating embodied actionability, knowledge, experimentation, and reasoning in self‑driving chemical laboratories. It contains 1,000 expert‑curated question‑answer pairs across 11 image and video task types, covering affordance grounding, trajectory planning, equipment and state recognition, safety, apparatus setup, operation, step reasoning, and temporal procedure reasoning. The benchmark is manually created and reviewed by chemistry and embodied AI experts, and it tests 28 different multimodal large language models in an offline, single‑turn setting.
arXiv Computer Vision
Sep 30
Real2Gym: Building Gyms from Videos, Bringing Skills to Robots
arXiv:2609.37089v1 Announce Type: new Abstract: Real-world videos provide rich demonstrations of manipulation, but turning them into reusable robot skills requires visually aligned environments, exec...
arXiv Computer Vision
Oct 28
LabWorld: Learning Interactive 4D Worlds for Scientific Experimentation
LabWorld is a Real2Sim framework that reconstructs interactive 4D laboratory worlds from monocular RGB video, producing reusable 3D assets, metric scenes, time‑varying object states, and procedure events. By leveraging multi‑frame observations and motion reconstruction that combines visual, geometric, and event constraints, LabWorld outperforms existing baselines on real pipetting and vortexing tasks, achieving higher Mask IoU and PCK‑AUC scores. The framework enables explicit, editable state representation for replay, inspection, and future embodied scientific systems.