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Found 6 papers, 4 papers with code
One Agent Too Many: User Perspectives on Approaches to Multi-agent Conversational AI
Conversational agents have been gaining increasing popularity in recent years.
Rule By Example: Harnessing Logical Rules for Explainable Hate Speech Detection
In this paper, we present Rule By Example (RBE): a novel exemplar-based contrastive learning approach for learning from logical rules for the task of textual content moderation.
Label Agnostic Pre-training for Zero-shot Text Classification
In addition, depending on the aspect (sentiment, topic, etc.)
One Agent To Rule Them All: Towards Multi-agent Conversational AI
To address these problems, we introduce a new task BBAI: Black-Box Agent Integration, focusing on combining the capabilities of multiple black-box CAs at scale.
Ranked #1 on
Multi-agent Integration
on BBAI Dataset
Conversational Response Selection
Multi-agent Integration
+1
Towards Personalized Intelligence at Scale
Personalized Intelligence (PI) is the problem of providing customized AI experiences tailored to each individual user.
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
We find that while the classifiers perform well on in-scope intent classification, they struggle to identify out-of-scope queries.
