efficiency
CVPR_workshop_efficiencyVLMnewsmner-data-efficiencytool-call-efficiency
tool-call-efficiency
Made with the whileai SDK · Collections: Efficiency, Start here: foundational post-training datasets
Teach an agent to make every tool call count.
An agent that calls a tool twice with the same arguments, looks up what
the user just told it, or keeps calling after the task is done is slow,
expensive, and harder to trust. Ask a base Qwen3-4B to work through
1,133 tool-using tasks across six agents and it does this a lot:
only 52% of its 6,681 rollouts finish… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/tool-call-efficiency.enzyme_catalytic_efficiency
Dataset Card for Enzyme Catalytic Efficiency Dataset
Dataset Summary
This task is focused on predicting $k_cat$ values, which are enzymatic turnover numbers denoting the maximum chemical conversion rate of a reaction, for metabolic enzymes originating from any organism. These predictions are based on substrate structures and protein sequences. The underlying importance of this task lies in its potential to yield high-throughput and accurate $k_cat$ predictions applicable… See the full description on the dataset page: https://huggingface.co/datasets/biomap-research/enzyme_catalytic_efficiency.perovskite-solar-cell-efficiency-autoresearch
🔬 Perovskite Solar Cell Text Corpus for Karpathy's autoresearch
A 98.9 MB text corpus of perovskite solar cell scientific literature formatted for direct use with karpathy/autoresearch — the autonomous LLM-driven hyperparameter search framework that trains a GPT from scratch and has an AI agent iteratively modify train.py to minimize val_bpb (bits per byte).
📊 Dataset Stats
Metric
Value
Total documents
19,730
Total text
98.9 MB (~103M characters)… See the full description on the dataset page: https://huggingface.co/datasets/CollinL/perovskite-solar-cell-efficiency-autoresearch.SiN-photonic-waveguide-loss-efficiency
💎 SiN Photonic Waveguide Loss & Efficiency Dataset
🔬 90,000 synthetic rows of silicon nitride (Si₃N₄) waveguide parameters linking geometry, fabrication, and operating conditions to loss and efficiency metrics, for regression modeling, simulation, and fine-tuning.
⚠️ Disclaimer: All rows are synthetically generated. Parameter ranges are informed by published SiN platform values, but no row is a foundry measurement. The data_source column is a schema field; every row in this… See the full description on the dataset page: https://huggingface.co/datasets/Taylor658/SiN-photonic-waveguide-loss-efficiency.