https://github.com/rutvikvijjali/COVID-19-Claims-Dataset
공식 코드Two Stage Transformer Model for COVID-19 Fake News Detection and Fact Checking
Papers with Code 아카이브
Natural Language Inference
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given a "premise".
Example:
| Premise | Label | Hypothesis |
|---|---|---|
| A man inspects the uniform of a figure in some East Asian country. | contradiction | The man is sleeping. |
| An older and younger man smiling. | neutral | Two men are smiling and laughing at the cats playing on the floor. |
| A soccer game with multiple males playing. | entailment | Some men are playing a sport. |
Approaches used for NLI include earlier symbolic and statistical approaches to more recent deep learning approaches. Benchmark datasets used for NLI include SNLI, MultiNLI, SciTail, among others. You can get hands-on practice on the SNLI task by following this d2l.ai chapter.
Further readings:
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rycolab/differentiable-subset-pruning
공식 코드https://github.com/rycolab/differential-subset-pruning
공식 코드https://github.com/ryokamoi/wice
공식 코드https://github.com/s-l-chausson/easyclaimsdetection
공식 코드Detecting Statements in Text: A Domain-Agnostic Few-Shot Solution
https://github.com/s-nlp/dont-fight-hallucinations
공식 코드Don't Fight Hallucinations, Use Them: Estimating Image Realism using NLI over Atomic Facts
https://github.com/s65b40/prompt_n_paraphrase
공식 코드Prompt Combines Paraphrase: Teaching Pre-trained Models to Understand Rare Biomedical Words
https://github.com/saccharomycetes/text-based-traffic
공식 코드Utilizing Background Knowledge for Robust Reasoning over Traffic Situations
https://github.com/saccharomycetes/text-based-traffic-understanding
공식 코드https://github.com/salesforce/DNNC-few-shot-intent
공식 코드Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
https://github.com/salesforce/DocNLI
공식 코드DocNLI: A Large-scale Dataset for Document-level Natural Language Inference
https://github.com/salesforce/UniversalFewShotNLP
공식 코드https://github.com/salesforce/VD-BERT
공식 코드https://github.com/salesforce/cove
공식 코드https://github.com/salesforce/decaNLP
공식 코드The Natural Language Decathlon: Multitask Learning as Question Answering
https://github.com/samyateia/bioasq
공식 코드https://github.com/sara-rajaee/reverse_bias
공식 코드Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language Inference
https://github.com/sberbank-ai-lab/RuMedBench
공식 코드RuMedBench: A Russian Medical Language Understanding Benchmark
https://github.com/scai-conf/scai-qrecc-21
공식 코드https://github.com/sding11/RAG-VR
공식 코드RAG-VR: Leveraging Retrieval-Augmented Generation for 3D Question Answering in VR Environments
https://github.com/seamoke/Human-Think-Language
공식 코드How Do Humans Write Code? Large Models Do It the Same Way Too
https://github.com/seonghyeonye/flipped-learning
공식 코드Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners
https://github.com/seongminp/lime
공식 코드https://github.com/shabnam-b/elqa
공식 코드ELQA: A Corpus of Metalinguistic Questions and Answers about English
https://github.com/shahriarnz14/tldr-t5-generated-clinical-language-for-deberta-report-analysis
공식 코드TLDR at SemEval-2024 Task 2: T5-generated clinical-Language summaries for DeBERTa Report Analysis
https://github.com/shanyas10/Evaluating-gender-bias
공식 코드https://github.com/shijie-wu/crosslingual-nlp
공식 코드Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT
https://github.com/shininglab/cat
공식 코드Counterfactual Adversarial Learning with Representation Interpolation
https://github.com/shreydesai/calibration
공식 코드https://github.com/shuaitang/TPRU
공식 코드A Simple Recurrent Unit with Reduced Tensor Product Representations
https://github.com/shuohangwang/Cross-Thought
공식 코드https://github.com/shuohangwang/SeqMatchSeq
공식 코드https://github.com/shuohangwang/mprc
공식 코드R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering
https://github.com/sindhukrao/llm_temporal_bias
공식 코드Unveiling Divergent Inductive Biases of LLMs on Temporal Data
https://github.com/sinovation/ZEN
공식 코드ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
https://github.com/sjtu-lit/syncse
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.