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Found 6 papers, 5 papers with code
Learning from Emotions, Demographic Information and Implicit User Feedback in Task-Oriented Document-Grounded Dialogues
The success of task-oriented and document-grounded dialogue systems depends on users accepting and enjoying using them.
Dior-CVAE: Pre-trained Language Models and Diffusion Priors for Variational Dialog Generation
These models also suffer from posterior collapse, i. e., the decoder tends to ignore latent variables and directly access information captured in the encoder through the cross-attention mechanism.
The Devil is in the Details: On Models and Training Regimes for Few-Shot Intent Classification
First, the unexplored combination of the cross-encoder architecture (with parameterized similarity scoring function) and episodic meta-learning consistently yields the best FSIC performance.
One-shot to Weakly-Supervised Relation Classification using Language Models
Unfortunately, both annotation methodologies are costly and time-consuming since they depend on intensive human labour for annotation or for knowledge base creation.
DeepEventMine: end-to-end neural nested event extraction from biomedical texts
Motivation Recent neural approaches on event extraction from text mainly focus on flat events in general domain, while there are less attempts to detect nested and overlapping events.
Ranked #1 on
Event Extraction
on GENIA 2013
Revisiting Unsupervised Relation Extraction
Unsupervised relation extraction (URE) extracts relations between named entities from raw text without manually-labelled data and existing knowledge bases (KBs).
