Pinned Repositories
ASER
ASER (Activities, States, Events, and their Relations): a large-scale weighted eventuality knowledge graph.
CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计
DiscrimLoss
DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination
evals
Evals is a framework for evaluating OpenAI models and an open-source registry of benchmarks.
NoisywikiHow
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing (ACL2023 Findings)
NoisywikiHow-dataset
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing (ACL2023 Findings)
STGN-NoisyNER
Sub-experiment of "STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing" (EMNLP 2022) by Tingting Wu, Xiao Ding, Minji Tang, Hao Zhang, Bing Qin, Ting Liu.
STGN-sst
STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing (EMNLP 2022)
STGN-wikiHow
Sub-experiment of "STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing" (EMNLP 2022) by Tingting Wu, Xiao Ding, Minji Tang, Hao Zhang, Bing Qin, Ting Liu.
ULTRA
Uncertainty-guided Label Correction with Wavelet-transformed Discriminative Representation Enhancement
tangminji's Repositories
tangminji/NoisywikiHow
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing (ACL2023 Findings)
tangminji/STGN-sst
STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing (EMNLP 2022)
tangminji/NoisywikiHow-dataset
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing (ACL2023 Findings)
tangminji/DiscrimLoss
DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination
tangminji/Office-E5
Office E5 订阅，使用Github Action 自动调用API。By Java
tangminji/STGN-NoisyNER
Sub-experiment of "STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing" (EMNLP 2022) by Tingting Wu, Xiao Ding, Minji Tang, Hao Zhang, Bing Qin, Ting Liu.
tangminji/STGN-wikiHow
Sub-experiment of "STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing" (EMNLP 2022) by Tingting Wu, Xiao Ding, Minji Tang, Hao Zhang, Bing Qin, Ting Liu.
tangminji/ULTRA
Uncertainty-guided Label Correction with Wavelet-transformed Discriminative Representation Enhancement
tangminji/ASER
ASER (Activities, States, Events, and their Relations): a large-scale weighted eventuality knowledge graph.
tangminji/CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计
tangminji/evals
Evals is a framework for evaluating OpenAI models and an open-source registry of benchmarks.
tangminji/google-research
Google Research
tangminji/LA-beginner
tangminji/Lhy_Machine_Learning
李宏毅2021春季机器学习课程课件及作业
tangminji/ltp
Language Technology Platform
tangminji/Math-World
tangminji/Megatron-LM
Ongoing research training transformer models at scale
tangminji/ML2021-Spring
李宏毅 (Hung-Yi Lee) 機器學習 Machine Learning 2021 Spring
tangminji/ner_demo
按要求制作的ner_demo，后端暂时使用ltp获取结果，目前先使用固定的两个样例展示，
tangminji/openai-python
The OpenAI Python library provides convenient access to the OpenAI API from applications written in the Python language.
tangminji/MentorMix_pytorch
[MentorMix] "Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels" implemented in the PyTorch version.
tangminji/paddle-nmt
saved models
tangminji/plm-nlp-code
tangminji/scir-training-day
a small training program for new crews of HIT-SCIR
tangminji/tangminji.github.io
tangminji/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.