datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
magpie-reasoning-v1-10k-step-by-step-rationale-alpaca-format-llama3.1echr_rational
Dataset Card for echr_rational
Dataset Summary
Deconfounding Legal Judgment Prediction for European Court of Human
Rights Cases Towards Better Alignment with Experts
This work demonstrates that Legal Judgement Prediction systems without expert-informed adjustments can be vulnerable to shallow, distracting surface signals that arise from corpus construction, case distribution, and confounding factors. To mitigate this, we use domain expertise to strategically identify… See the full description on the dataset page: https://huggingface.co/datasets/TUMLegalTech/echr_rational.magpie-reasoning-v1-10k-step-by-step-rationale-alpaca-format-changedtokenmagpie-reasoning-v1-10k-step-by-step-rationale-alpaca-format-changedtoken-mistralsocio-moral-image-rationales
Socio-Moral Image Rationales
This is a collection of machine-generated and human-labeled explanations for immorality in images.
The images are source from the Socio-Moral Image Database (SMID) and limited to the ones displaying immoral content (SMID moral mean <= 2.0).
Sampled explanations were generated by vision-language model using the ILLUME paradigm presented in ILLUME: Rationalizing Vision-Language Models through Human Interactions.
Explanations are rated by human annotators… See the full description on the dataset page: https://huggingface.co/datasets/AIML-TUDA/socio-moral-image-rationales.ESG_ver1_rationaleclinical-intervention-rationale-construction-coherence-v0.1GoalJudge whether an intervention rationale matches the patient state.
Model must
identify missing rationale links
name competing hypotheses
flag risk tradeoffs
predict expected signal shift
UseTests construction-level clinical reasoning.
KorFinASC_ver1_rationale