datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
All-Prompt-Jailbreakeu-ai-act-article-50-scoreboard
Article 50 historical public-evidence snapshot
This work was produced through an AI-assisted workflow directed by the author. Historical work used Anthropic assistance; the retrospective correction uses OpenAI GPT-6, with separate bounded Gemini advice. All three providers have products in the scored set.
Purpose: provide the corrected paper's version 1.1 bundle under v1_1. Start with its README and correction note. The paper and deposit and GitHub repository identify the same… See the full description on the dataset page: https://huggingface.co/datasets/NMAIResearch/eu-ai-act-article-50-scoreboard.ArogyaBodha_ActCri
ArogyaBodha_ActCri
Parallel (wide) variant for the actor-critic framework; each row pairs a local-language case with its English translation. Splits: train ~32,250 / test 3,500 (symmetric 500-cid holdout).
Columns
Column
Type
Description
lid
Value('string')
Language-scoped id
language
Value('string')
Case language
Figure_A
Image(mode=None, decode=True)
Medical image
Figure_B
Image(mode=None, decode=True)
Medical image
Figure_C
Image(mode=None… See the full description on the dataset page: https://huggingface.co/datasets/iit-patna-cse-ai/ArogyaBodha_ActCri.sdxl-activation-steering
SDXL Image Activation Steering: Continuous Concept Trajectory Control
This repository demonstrates Representation Engineering and Activation Steering on Diffusion Models (SDXL Turbo) using PyTorch and Hugging Face diffusers on an NVIDIA H100 GPU.
⚡ How It Works
Instead of retraining a LoRA or using binary negative prompt weights, we extract continuous concept steering vectors:
vstyle=1N∑i=1N(ecyberpunk_neon(i)−egolden_hour(i))\mathbf{v}_{\text{style}} =… See the full description on the dataset page: https://huggingface.co/datasets/mayank-dubey-ai/sdxl-activation-steering.