Papers with Code 아카이브

Sentence Classification

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하위 태스크

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평가표

6

보존된 평가 기록

16

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/sayantan11995/event-timeline-generation-from-documents

공식 코드

Placing (Historical) Facts on a Timeline: A Classification cum Coref Resolution Approach

https://github.com/sciencenlp-lab/llm-ssc

공식 코드

Multi-label Sequential Sentence Classification via Large Language Model

https://github.com/sergioburdisso/pyss3

공식 코드

t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams

https://github.com/shininglab/cat

공식 코드

Counterfactual Adversarial Learning with Representation Interpolation

https://github.com/shuningjin/discrete-text-rep

공식 코드

Discrete Latent Variable Representations for Low-Resource Text Classification

https://github.com/slanglab/IndiaPoliceEvents

공식 코드

Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence

https://github.com/thefonseca/concept-guidelines

공식 코드

Can Large Language Models Follow Concept Annotation Guidelines? A Case Study on Scientific and Financial Domains

https://github.com/themody/nasforsentenceembeddingheads

공식 코드

Neural Architecture Search for Sentence Classification with BERT

https://github.com/ukplab/adasent

공식 코드

AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification

https://github.com/ulf1/sentence-embedding-evaluation-german

공식 코드

Rediscovering Hashed Random Projections for Efficient Quantization of Contextualized Sentence Embeddings

https://github.com/vyraun/dlp

공식 코드

On Dimensional Linguistic Properties of the Word Embedding Space

https://github.com/warnikchow/kcharemb

공식 코드

Investigating an Effective Character-level Embedding in Korean Sentence Classification

https://github.com/webis-de/acl22-revisiting-uncertainty-based-query-strategies-for-active-learning-with-transformers

공식 코드

Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers

https://github.com/xianjun-yang/pcmsp

공식 코드

PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text

https://github.com/yeziyi1998/uercm

공식 코드

Towards a Better Understanding Human Reading Comprehension with Brain Signals

https://github.com/yihongl1u/colexificationnet

공식 코드

Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification Graphs

https://github.com/zepingyu0512/in-context-mechanism

공식 코드

How do Large Language Models Learn In-Context? Query and Key Matrices of In-Context Heads are Two Towers for Metric Learning

https://dagshub.com/Dean/BioBERT-DAGsHub

BioBERT: a pre-trained biomedical language representation model for biomedical text mining

https://github.com/1wy/bert

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2023-MindSpore-1/ms-code-11

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2023-MindSpore-1/ms-code-12

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2023-MindSpore-1/ms-code-150

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2023-MindSpore-1/ms-code-56

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/bert

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2024-MindSpore-1/Code3/tree/main/scBERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/2miatran/Natural-Language-Processing

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/ABaldrati/MT-BERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/AGiannoutsos/COVID19-document-retrieval-with-BERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/AbhishekD15/Sentiment-Analysis_BERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/AdamStein97/Semi-Supervised-BERT-NER

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/AhmedYounes94/Semi-supervised-BERT-NER

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/Alihassan7726/Fine-tuning-BERT-for-semantic-sentence-pairs-classification

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/Alihassan7726/Multi-Class-classification-using-BERT-

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/Arthurizijar/Bert_Airport

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/ArvinZhuang/BiTAG

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/AtmaHou/MetaDialog

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.