pte
Datasets
All datasets matching “pte”DomainBed_OOP
DomainBed-(IP/OOP)
Dataset release for "Do Domain Generalization methods Generalize Beyond their Pre-training?"
Dataset Splits
The IP split is available in the ip directory.
The OOP split is available in the oop directory.
The Unsplit data is available in the all directory.
The Alignment Scores used to split the data are available in the alignmentscores directory.
Licenses
We release the dataset under the same terms as the original datasets we split, passing… See the full description on the dataset page: https://huggingface.co/datasets/PTeterwak/DomainBed_OOP.pt_exams
PHEB - Portuguese High School Exams MCQ
MCQ set of PHEB a collection of Portuguese exam questions for evaluating language models on academic knowledge on the Portuguese curriculum.
For more details, see the PHEB paper.
This dataset is provided as part of the AMALIA project and is included in AMALIA-Bench, a comprehensive benchmark suite for evaluating large language models on European Portuguese.
Citation
If you use this dataset or AMALIA in your work… See the full description on the dataset page: https://huggingface.co/datasets/amalia-llm/pt_exams.PTextprompts_gaia_5shot_3expDataset-PTEN_HUMAN
Description
This dataset contains signle site mutation of protein PTEN_HUMAN and the correspond mutation effect score from deep mutation scanning experiment.
Protein Format: AA sequence
Splits
traing: 3311
valid: 375
test: 410
Related paper
The dataset is from Deep generative models of genetic variation capture the effects of mutations.
Label
Label means mutation fitness score (protein stability) of each protein based on deep mutation scanning… See the full description on the dataset page: https://huggingface.co/datasets/SaProtHub/Dataset-PTEN_HUMAN.action-reward-models-data
Action Reward Models for Web Agents
Minimal, self-contained repo for the action reward model (ARM) study:
generate per-step candidate-action data from a web-agent policy, train two
kinds of reward models on teacher labels, and use them to pick actions at
inference time. Everything here was extracted from two production pipelines
("eras") and trimmed to the essential path.
Written to be read by an AI assistant picking this up cold — file paths,
gotchas, and provenance are spelled… See the full description on the dataset page: https://huggingface.co/datasets/PTeterwak/action-reward-models-data.