https://github.com/declare-lab/aste-rl
공식 코드Aspect Sentiment Triplet Extraction Using Reinforcement Learning
Papers with Code 아카이브
Sentence
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/declare-lab/doublemix
공식 코드DoubleMix: Simple Interpolation-Based Data Augmentation for Text Classification
https://github.com/declare-lab/relationprompt
공식 코드https://github.com/declare-lab/segue
공식 코드Sentence Embedder Guided Utterance Encoder (SEGUE) for Spoken Language Understanding
https://github.com/declare-lab/sentence-ordering
공식 코드STaCK: Sentence Ordering with Temporal Commonsense Knowledge
https://github.com/declare-lab/team
공식 코드https://github.com/declare-lab/vip
공식 코드Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding
https://github.com/deep-spin/robust_mt_evaluation
공식 코드BLEU Meets COMET: Combining Lexical and Neural Metrics Towards Robust Machine Translation Evaluation
https://github.com/deep-spin/scheduled-sampling-transformers
공식 코드https://github.com/deep-spin/ssm-mt
공식 코드How Effective are State Space Models for Machine Translation?
https://github.com/deep-spin/treqa
공식 코드Do LLMs Understand Your Translations? Evaluating Paragraph-level MT with Question Answering
https://github.com/deeplearnxmu/bigvideo-vmt
공식 코드BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation
https://github.com/deeplearnxmu/dmd
공식 코드A Dual-Perspective Metaphor Detection Framework Using Large Language Models
https://github.com/deeplearnxmu/irseg
공식 코드Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
https://github.com/deeplearnxmu/kgr-4
공식 코드KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense Generation
https://github.com/deepmind/svo_probes
공식 코드https://github.com/deepplants/vit-pcm
공식 코드https://github.com/deepsemantic/image_captioning
공식 코드https://github.com/deepsentiment/deepsentiment
공식 코드Multimodal Sentiment Analysis To Explore the Structure of Emotions
https://github.com/dengyang17/MTQA
공식 코드https://github.com/dennisrv/iail2022
공식 코드https://github.com/derekhoward/Reachout_triage
공식 코드Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study
https://github.com/dev-chauhan/PQG-pytorch
공식 코드Revisiting Paraphrase Question Generator using Pairwise Discriminator
https://github.com/dhirlea/contextual_sentence_classification
공식 코드Contextual Sentence Classification: Detecting Sustainability Initiatives in Company Reports
https://github.com/dialogue-evaluation/RuOpinionNE-2024
공식 코드RuOpinionNE-2024: Extraction of Opinion Tuples from Russian News Texts
https://github.com/dialogue-evaluation/rusentne-evaluation
공식 코드RuSentNE-2023: Evaluating Entity-Oriented Sentiment Analysis on Russian News Texts
https://github.com/diccooo/Deep_Enhanced_Repr_for_IDRR
공식 코드Deep Enhanced Representation for Implicit Discourse Relation Recognition
https://github.com/didzis/smatchTools
공식 코드https://github.com/didzis/tensorflowAMR
공식 코드https://github.com/diegma/neural-dep-srl
공식 코드Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling
https://github.com/dilkas/crane
공식 코드https://github.com/dinghanshen/Cutoff
공식 코드https://github.com/dipta007/semeval24-task8
공식 코드https://github.com/diqiuzhuanzhuan/semeval-2023
공식 코드https://github.com/dirkiedai/sk-mt
공식 코드https://github.com/disl-lab/finesure-acl24
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.