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Found 6 papers, 1 papers with code
Non-contrastive sentence representations via self-supervision
Sample contrastive methods, typically referred to simply as contrastive are the foundation of most unsupervised methods to learn text and sentence embeddings.
Distillation of encoder-decoder transformers for sequence labelling
Driven by encouraging results on a wide range of tasks, the field of NLP is experiencing an accelerated race to develop bigger language models.
Disentangling Online Chats with DAG-Structured LSTMs
In this paper, we apply DAG-LSTMs to the conversation disentanglement task.
Hierarchical clustering in particle physics through reinforcement learning
Particle physics experiments often require the reconstruction of decay patterns through a hierarchical clustering of the observed final-state particles.
Dialogue Act Classification in Group Chats with DAG-LSTMs
In this paper, we introduce a new model architecture, directed-acyclic-graph LSTM (DAG-LSTM) for DA classification.
Inferring the quantum density matrix with machine learning
We also introduce quantum flows, the quantum analog of normalizing flows, which can be used to increase the expressivity of this variational family.
