Search Results for author:
Found 14 papers, 6 papers with code
Feature Activation Map: Visual Explanation of Deep Learning Models for Image Classification
However, all the CAM-based methods (e. g., CAM, Grad-CAM, and Relevance-CAM) can only be used for interpreting CNN models with fully-connected (FC) layers as a classifier.
A resource-efficient deep learning framework for low-dose brain PET image reconstruction and analysis
18F-fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET) imaging usually needs a full-dose radioactive tracer to obtain satisfactory diagnostic results, which raises concerns about the potential health risks of radiation exposure, especially for pediatric patients.
A Compositional Feature Embedding and Similarity Metric for Ultra-Fine-Grained Visual Categorization
Motivated by these issues, this paper proposes a novel compositional feature embedding and similarity metric (CECS).
TGEA: An Error-Annotated Dataset and Benchmark Tasks for TextGeneration from Pretrained Language Models
Each error is hence manually labeled with comprehensive annotations, including the span of the error, the associated span, minimal correction to the error, the type of the error, and rationale behind the error.
PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
To enhance the generalization ability of PanGu-$\alpha$, we collect 1. 1TB high-quality Chinese data from a wide range of domains to pretrain the model.
Ranked #1 on
Reading Comprehension (One-Shot)
on DuReader
Cloze (multi-choices) (Few-Shot)
Cloze (multi-choices) (One-Shot)
+19
Probabilistically Masked Language Model Capable of Autoregressive Generation in Arbitrary Word Order
Masked language model and autoregressive language model are two types of language models.
Zero-Shot Paraphrase Generation with Multilingual Language Models
Leveraging multilingual parallel texts to automatically generate paraphrases has drawn much attention as size of high-quality paraphrase corpus is limited.
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
The pre-trained language models have achieved great successes in various natural language understanding (NLU) tasks due to its capacity to capture the deep contextualized information in text by pre-training on large-scale corpora.
GPT-based Generation for Classical Chinese Poetry
We present a simple yet effective method for generating high quality classical Chinese poetry with Generative Pre-trained Language Model (GPT).
QuaSE: Sequence Editing under Quantifiable Guidance
For example, an input sequence could be a word sequence, such as review sentence and advertisement text.
QuaSE: Accurate Text Style Transfer under Quantifiable Guidance
For example, an input sequence could be a word sequence, such as review sentence and advertisement text.
Abstractive Multi-Document Summarization via Phrase Selection and Merging
We propose an abstraction-based multi-document summarization framework that can construct new sentences by exploring more fine-grained syntactic units than sentences, namely, noun/verb phrases.
Reader-Aware Multi-Document Summarization via Sparse Coding
We propose a new MDS paradigm called reader-aware multi-document summarization (RA-MDS).
