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Angeliki Metallinou

4 accepted papers

2024

FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking

EMNLP 2024finding

API call generation is the cornerstone of large language models’ tool-using ability that provides access to the larger world. However, existing supervised and in-context learning approaches suffer from high training costs, poor data efficiency, and generated API calls that can be unfaithful to the A…

2023

Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users

EMNLP 2023long findings

While most task-oriented dialogues assume conversations between the agent and one user at a time, dialogue systems are increasingly expected to communicate with multiple users simultaneously who make decisions collaboratively. To facilitate development of such systems, we release the Multi-User Mult…

Cited by 0SourcecodeScholar
2023

Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs

ACL 2023industry

Measurement of interaction quality is a critical task for the improvement of large-scale spoken dialog systems. Existing approaches to dialog quality estimation either focus on evaluating the quality of individual turns, or collect dialog-level quality measurements from end users immediately followi…

Cited by 3SourcePDFScholar
2021

Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems

NAACL 2021system demonstrations

Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Training each component requires annotations which are hard to obtain for every new domain, limiting scalability of such sys…

Cited by 22SourcePDFScholar