3 accepted papers
The factuality of large language model (LLMs) tends to decay over time since events posterior to their training are “unknown” to them. One way to keep models up-to-date could be factual update: the task of inserting, replacing, or removing certain simple (atomic) facts within the model. To study thi…
Current sequence tagging models based on Deep Neural Network models with pretrained language models achieve almost perfect results on many SLU benchmarks with a flat semantic annotation at the token level such as ATIS or SNIPS. When dealing with more complex human-machine interactions (multi-domain,…
In the context of contact centers, customers' satisfaction after a conversation with an agent is a critical issue which has to be collected in order to detect problems and improve quality of service. Automatically predicting customer satisfaction directly from system logs, without any survey or manu…