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Found 8 papers, 0 papers with code
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models
Our target of study includes Output Distribution (OD) transfer, Hidden State (HS) transfer with various layer mapping strategies, and Multi-Head Attention (MHA) transfer based on MiniLMv2.
CoSiNES: Contrastive Siamese Network for Entity Standardization
Entity standardization maps noisy mentions from free-form text to standard entities in a knowledge base.
Neural Architecture Search for Effective Teacher-Student Knowledge Transfer in Language Models
In each episode of the search process, a NAS controller predicts a reward based on the distillation loss and latency of inference.
Large Scale Neural Architecture Search with Polyharmonic Splines
Neural Architecture Search (NAS) is a powerful tool to automatically design deep neural networks for many tasks, including image classification.
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
The typical way of conducting large scale NAS is to search for an architectural building block on a small dataset (either using a proxy set from the large dataset or a completely different small scale dataset) and then transfer the block to a larger dataset.
Covering the News with (AI) Style
We introduce a multi-modal discriminative and generative frame-work capable of assisting humans in producing visual content re-lated to a given theme, starting from a collection of documents(textual, visual, or both).
Diversity in Faces
We expect face recognition to work equally accurately for every face.
Cultural Vocal Bursts Intensity Prediction
Face Recognition
+1
Automatic Curation of Golf Highlights using Multimodal Excitement Features
The production of sports highlight packages summarizing a game's most exciting moments is an essential task for broadcast media.
