SciHorizon-eLab: An Agentic Protocol-to-Task Compiler for Scalable Benchmarking of Scientific Embodied Agents
On the map: LLM agents and tool use → Multimodal and embodied agents also fits: Agent skill learning and evolution
Abstract (arXiv)
Embodied agents offer a promising route to automating scientific experimentation, yet their progress is constrained by the lack of reliable and systematic evaluation environments. Existing simulation-based laboratory benchmarks rely heavily on manual task engineering, making it challenging to systematically compile diverse scientific protocols into executable and verifiable embodied tasks at scale. To address this challenge, we introduce SciHorizon-eLab, an agentic protocol-to-task compiler that formulates scientific embodied task construction as a compilation problem. Given a natural-language protocol of scientific experiments, SciHorizon-eLab progressively compiles laboratory protocols into semantic-preserving embodied tasks through semantic grounding, executable task synthesis, and multi-stage simulation-based certification. The system generates semantically grounded environments, executable manipulation programs, and step-level success specifications, while enabling reproducible generation of expert demonstrations and execution traces. Using this pipeline, we further construct BenchName, a ready-to-use benchmark comprising 300 certified tasks across diverse laboratory operations. It supports HIL task execution, reproducible expert-demonstration generation, and ordered step-level evaluation. Across representative tasks, the strongest policy attains an average success rate of only 49.7%, with further evaluations revealing pronounced weaknesses in human and embodied agent coordination. We publicly release the code, benchmark data, and evaluation toolkit at https://github.com/SciHorizon-elab/SciHorizon-elab.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 17 of its 28 references that are in the map. First posted on arXiv 25 Sep 2026.
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17 of 28 references.
References · 17
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- 2023ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skillscited by 313
5 more
- 2023RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulationcited by 206
- 2024VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Taskscited by 171
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- 2025LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agentscited by 14
- 2026LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratoriescited by 3
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- 2026LAP: An Agent-to-Instrument Protocol for Autonomous Science
- 2026ProtoAct: Turning Wet-Lab Protocols into Embodied Robotic Actions
- 2026Embodied Science: Closing the Discovery Loop with Agentic Embodied AI
- 2026Compiling and Benchmarking Task-State Horizons for Embodied Agents
- 2026ETA: A New Agentic Paradigm for Embodied Tasks