DeBERTa-v3
deberta-v3-12660b04·3 events·first seen 25d agoAliases: DeBERTa-v3, DeBERTa-v2
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Systematic Study of Schwartz Value Detection in Political Texts: Context, Scale, and Moral Knowledge
This paper investigates when additional context, larger models, or retrieved moral knowledge improve detection of Schwartz human values in political text using the ValueEval benchmark format. Key findings show that full-document context helps supervised DeBERTa encoders (+3.8–4.8 macro-F1) but not zero-shot LLMs, while RAG with a curated moral knowledge base consistently benefits all model families under early fusion. Scaling model size does not guarantee gains, and simple early fusion outperforms more complex RAG variants. The study recommends jointly evaluating context, knowledge, and model family rather than assuming larger inputs or models universally improve value-sensitive NLP.
Meta releases Llama Prompt Guard 2 (86M) for prompt injection and jailbreak detection
Meta released Llama Prompt Guard 2-86M, a DeBERTa-v2-based text classification model on Hugging Face designed for safety filtering, specifically prompt injection and jailbreak detection. The model is tagged with llama4, suggesting it is part of the Llama 4 safety tooling ecosystem. With over 122K downloads, it has seen meaningful early adoption.
Meta releases Llama Prompt Guard 2 (22M) safety classifier on Hugging Face
Meta released Llama Prompt Guard 2-22M, a lightweight 22-million-parameter text classification model for prompt safety, published on Hugging Face under the meta-llama organization. The model is based on DeBERTa-v2 architecture and tagged for safety use cases including prompt injection and jailbreak detection. It is part of the Llama 4 safety tooling ecosystem and supports English and French.