Papers with understanding capabilities

2 papers
Fast and Scalable Expansion of Natural Language Understanding Functionality for Intelligent Agents (N18-3)

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Challenge: a recent paper describes efficient deep neural network architectures for expanding natural language capabilities of virtual agents.
Approach: They propose deep neural network architectures that maximize re-use available resources . they use data from Amazon Alexa to accelerate expansion of new natural language domains .
Outcome: The proposed methods increase accuracy in low resource settings and enable rapid development with less data.
TriageAgent: Towards Better Multi-Agents Collaborations for Large Language Model-Based Clinical Triage (2024.findings-emnlp)

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Challenge: escalation in emergency department patient visits poses challenges to efficient clinical management . Currently, hospitals rely on human experts to review clinical notes and determine case urgency .
Approach: a team of researchers develop a multi-agent framework to enhance collaborative decision-making in clinical triage.
Outcome: The proposed framework outperforms state-of-the-art LLM-based methods on three clinical triage test sets.

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