Search Results for author:
Found 4 papers, 1 papers with code
Asynchronous Convergence in Multi-Task Learning via Knowledge Distillation from Converged Tasks
However, one issue that often arises in MTL is the convergence speed between tasks varies due to differences in task difficulty, so it can be a challenge to simultaneously achieve the best performance on all tasks with a single model checkpoint.
DynaMaR: Dynamic Prompt with Mask Token Representation
In this paper, we propose an improvement to prompt-based fine-tuning that addresses these two issues.
Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations
Our dataset consists of amino acid sequences, Q8 secondary structures, position specific scoring matrices, multiple sequence alignment co-evolutionary features, backbone atom distance matrices, torsion angles, and 3D coordinates.
Similar but not the Same: Word Sense Disambiguation Improves Event Detection via Neural Representation Matching
Event detection (ED) and word sense disambiguation (WSD) are two similar tasks in that they both involve identifying the classes (i. e. event types or word senses) of some word in a given sentence.
