https://github.com/strong-ai-lab/logical-equivalence-driven-amr-data-augmentation-for-representation-learning
공식 코드Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/studio-ousia/ease
공식 코드EASE: Entity-Aware Contrastive Learning of Sentence Embedding
https://github.com/studio-ousia/ntee
공식 코드Learning Distributed Representations of Texts and Entities from Knowledge Base
https://github.com/su0315/discourse_context_mt
공식 코드Context-aware Neural Machine Translation for English-Japanese Business Scene Dialogues
https://github.com/subhc/clever
공식 코드The Curious Layperson: Fine-Grained Image Recognition without Expert Labels
https://github.com/sufenlp/accalign
공식 코드Multilingual Sentence Transformer as A Multilingual Word Aligner
https://github.com/suhara/sourcesum
공식 코드https://github.com/suman101112/fire-2020-Dravidian-CodeMix
공식 코드https://github.com/sumnerlab/talkmoves
공식 코드https://github.com/sunbowliu/ptvsbt
공식 코드On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation
https://github.com/sungjinnam/contextual_informativeness
공식 코드https://github.com/sungjoonpark/emotiondetection
공식 코드https://github.com/sunilitggu/DDI-extraction-through-LSTM
공식 코드Drug-Drug Interaction Extraction from Biomedical Text Using Long Short Term Memory Network
https://github.com/sunjiao123sun/llm-controlgen
공식 코드Evaluating Large Language Models on Controlled Generation Tasks
https://github.com/sunoh-kim/pps
공식 코드https://github.com/sunyilgdx/prompts4keras
공식 코드https://github.com/sunzewei2715/Doc2Doc_NMT
공식 코드https://github.com/suprityoung/faima
공식 코드FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis
https://github.com/supstarzh/whitenedcse
공식 코드https://github.com/surabhisnath/creative_process
공식 코드Characterising the Creative Process in Humans and Large Language Models
https://github.com/sushmaakoju/acl2023-nlrse-clulab-sicck-dataset
공식 코드Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference
https://github.com/svip-lab/weaksvr
공식 코드Weakly Supervised Video Representation Learning with Unaligned Text for Sequential Videos
https://github.com/swarnahub/summarizationprograms
공식 코드Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees
https://github.com/sweetpeach/ReCode
공식 코드https://github.com/swisscom/ai-research-keyphrase-extraction
공식 코드Simple Unsupervised Keyphrase Extraction using Sentence Embeddings
https://github.com/swyoon/aaai2021-scene-graph-img-retr
공식 코드Image-to-Image Retrieval by Learning Similarity between Scene Graphs
https://github.com/synapse-developpement/DiscSense
공식 코드https://github.com/synapse-developpement/Discovery
공식 코드Mining Discourse Markers for Unsupervised Sentence Representation Learning
https://github.com/syw1996/SCIR-TG-Data2text-Bi-Aspect
공식 코드Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation
https://github.com/szxiangjn/any-shot-data2text
공식 코드ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models
https://github.com/t-i-p/hope-speech-detection-on-social-media-platforms
공식 코드https://github.com/t-zetsu/EditConstrainedDecoding
공식 코드https://github.com/tadeephuy/vimq
공식 코드ViMQ: A Vietnamese Medical Question Dataset for Healthcare Dialogue System Development
https://github.com/tafseer-nayeem/BengaliReadability
공식 코드Simple or Complex? Learning to Predict Readability of Bengali Texts
https://github.com/tag-and-generate/Politeness-Transfer-A-Tag-and-Generate-Approach
공식 코드https://github.com/tagoyal/dae-factuality
공식 코드Evaluating Factuality in Generation with Dependency-level Entailment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.