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Found 9 papers, 0 papers with code
Source Prompt: Coordinated Pre-training of Language Models on Diverse Corpora from Multiple Sources
Pre-trained language models (PLMs) have established the new paradigm in the field of NLP.
Progressive extension of reinforcement learning action dimension for asymmetric assembly tasks
Reinforcement learning (RL) is always the preferred embodiment to construct the control strategy of complex tasks, like asymmetric assembly tasks.
Feature-Based Compliance Control for Peg-in-Hole Assembly with Clearance or Interference Fit
This paper aims at solving mass precise peg-in-hole assembly.
A User-experience Driven SSIM-Aware Adaptation Approach for DASH Video Streaming
This mechanism impacts greatly on the overall Quality of Experience (QoE) of the video streaming.
SSIM
Multimedia
R3 Adversarial Network for Cross Model Face Recognition
The core of this problem is to make features extracted from different models comparable.
Learning to Auto Weight: Entirely Data-driven and Highly Efficient Weighting Framework
Example weighting algorithm is an effective solution to the training bias problem, however, most previous typical methods are usually limited to human knowledge and require laborious tuning of hyperparameters.
Dynamic Spatio-temporal Graph-based CNNs for Traffic Prediction
To capture the graph dynamics, we use the graph prediction stream to predict the dynamic graph structures, and the predicted structures are fed into the flow prediction stream.
Sampled in Pairs and Driven by Text: A New Graph Embedding Framework
TGE-PS uses Pairs Sampling (PS) to improve the sampling strategy of RW, being able to reduce ~99% training samples while preserving competitive performance.
Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition
We study the problem of named entity recognition (NER) from electronic medical records, which is one of the most fundamental and critical problems for medical text mining.
Medical Named Entity Recognition
named-entity-recognition
+3
