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TaskDiff: A Similarity Metric for Task-Oriented Conversations
The popularity of conversational digital assistants has resulted in the availability of large amounts of conversational data which can be utilized for improved user experience and personalized response generation.
DiSTRICT: Dialogue State Tracking with Retriever Driven In-Context Tuning
Dialogue State Tracking (DST), a key component of task-oriented conversation systems, represents user intentions by determining the values of pre-defined slots in an ongoing dialogue.
FedGen: Generalizable Federated Learning for Sequential Data
Existing federated learning models that follow the standard risk minimization paradigm of machine learning often fail to generalize in the presence of spurious correlations in the training data.
A Case for Business Process-Specific Foundation Models
The inception of large language models has helped advance state-of-the-art performance on numerous natural language tasks.
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