13 citations · 14 across the 6 of their papers we have counts for
8 papers
Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation
Genglin Liu, Muye Zhang, Krishnamurthy Viswanathan +5
Multimodal Large Language Models (MLLMs) are increasingly deployed for nuanced content safety and moderation tasks, yet they remain vulnerable to adversarial attacks and out-of-dis…
Agile Deliberation: Concept Deliberation for Subjective Visual Classification
Leijie Wang, Otilia Stretcu, Wei Qiao +7
From content moderation to content curation, applications requiring vision classifiers for visual concepts are rapidly expanding. Existing human-in-the-loop approaches typically as…
Zero-Shot Image Moderation in Google Ads with LLM-Assisted Textual Descriptions and Cross-modal Co-embeddings
Enming Luo, Wei Qiao, Katie Warren +7
We present a scalable and agile approach for ads image content moderation at Google, addressing the challenges of moderating massive volumes of ads with diverse content and evolvin…
Why Fine-grained Labels in Pretraining Benefit Generalization?
Guan Zhe Hong, Yin Cui, Ariel Fuxman +2
Recent studies show that pretraining a deep neural network with fine-grained labeled data, followed by fine-tuning on coarse-labeled data for downstream tasks, often yields better…
Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use
Imad Eddine Toubal, Aditya Avinash, Neil Gordon Alldrin +10
From content moderation to wildlife conservation, the number of applications that require models to recognize nuanced or subjective visual concepts is growing. Traditionally, devel…
Scaling Up LLM Reviews for Google Ads Content Moderation
Wei Qiao, Tushar Dogra, Otilia Stretcu +11
Large language models (LLMs) are powerful tools for content moderation, but their inference costs and latency make them prohibitive for casual use on large datasets, such as the Go…