A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
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2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Obj-Disco decomposes LLM alignment reward signals into sparse weighted combinations of interpretable natural language objectives via iterative analysis of behavioral changes across checkpoints, capturing over 90% of observed reward behavior.
citing papers explorer
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Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global South
A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
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Discovering Implicit Large Language Model Alignment Objectives
Obj-Disco decomposes LLM alignment reward signals into sparse weighted combinations of interpretable natural language objectives via iterative analysis of behavioral changes across checkpoints, capturing over 90% of observed reward behavior.