https://github.com/NVIDIA/NeMo-Skills
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
Papers with Code 아카이브
Question Answering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 19
- 평가표
- 153
- 보존된 평가 기록
- 1,781
Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
( Image credit: SQuAD )
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/NVIDIA/Star-Attention
BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack
https://github.com/NVIDIA/sentiment-discovery
https://github.com/Nalydy/doc2vec
https://github.com/NathanDuran/Sentence-Encoding-for-DA-Classification
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/Negus25/GAT-Mindspore
https://github.com/NehaTamore/TextSimilarity
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Neoanarika/torchexplainer
https://github.com/Nilanshrajput/Intent_classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Nimesh-Patel/BERT
https://github.com/Nimesh-Patel/text-to-text-transfer-transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/NisansaDdS/Some-Languages-are-More-Equal-than-Others
Systematic Inequalities in Language Technology Performance across the World's Languages
https://github.com/NormXU/ERNIE-Layout-Pytorch
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding
https://github.com/Nstats/bert_MRC
https://github.com/Nstats/bert_senti_analysis_ch
https://github.com/Nstats/my_bert
https://github.com/NydiaAI/g-mlp-tensorflow
https://github.com/OPAYA/Transformer
https://github.com/OPTAMI/OPTAMI
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization
https://github.com/Oichii/resnet3D_pulse
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?
https://github.com/OlavHN/attention-over-attention
Attention-over-Attention Neural Networks for Reading Comprehension
https://github.com/OpenGVLab/TimeSuite
TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning
https://github.com/OpenNLPhub/WebQA-Using-DGCNN
Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering
https://github.com/OpenSourceAI/sota-server
https://github.com/Osobarako/alduswarrensewell
https://github.com/OweysMomenzada/Evergreen-Content-Classifier-for-german-Text
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/PKU-YuanGroup/LLMBind
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/PKU-YuanGroup/MoE-LLaVA
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/POLane16/DIAG
Stochastic subgradient method converges at the rate $O(k^{-1/4})$ on weakly convex functions
https://github.com/PaddlePaddle/FleetX/blob/develop/examples/resnet/train_fleet_lamb.py
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
https://github.com/PaddlePaddle/FleetX/tree/develop/examples/hybrid_parallelism
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
https://github.com/PaddlePaddle/FleetX/tree/develop/examples/static/gpt
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/PaddlePaddle/PaddleNLP
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/PaddlePaddle/PaddleNLP/blob/develop/paddlenlp/transformers/albert/modeling.py
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/PaddlePaddle/PaddleNLP/blob/develop/paddlenlp/transformers/distilbert/modeling.py
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.