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Found 7 papers, 3 papers with code
Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning Perspective
We argue that the imbalance between old task and new task data contributes to forgetting of the old tasks.
Dynamic Generation of Personalities with Large Language Models
We propose a new metric to assess personality generation capability based on this evaluation method.
HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts
The Mixture of Experts (MoE) for language models has been proven effective in augmenting the capacity of models by dynamically routing each input token to a specific subset of experts for processing.
Shortcut Sequence Tagging
To simply the stacked architecture, we propose a framework called shortcut block, which is a marriage of the gating mechanism and shortcuts, while discarding the self-connected part in LSTM cell.
An Empirical Exploration of Skip Connections for Sequential Tagging
In this paper, we empirically explore the effects of various kinds of skip connections in stacked bidirectional LSTMs for sequential tagging.
A Dynamic Window Neural Network for CCG Supertagging
These motivate us to build a supertagger with a dynamic window approach, which can be treated as an attention mechanism on the local contexts.
