https://github.com/kareldo/wl-coref
공식 코드CAW-coref: Conjunction-Aware Word-level Coreference Resolution
Papers with Code 아카이브
Coreference Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 16
- 보존된 평가 기록
- 154
Coreference resolution is the task of clustering mentions in text that refer to the same underlying real world entities.
Example:
+-----------+
| |
I voted for Obama because he was most aligned with my values", she said.
| | |
+-------------------------------------------------+------------+
"I", "my", and "she" belong to the same cluster and "Obama" and "he" belong to the same cluster.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kawshikmanikantan/identifyme
공식 코드IdentifyMe: A Challenging Long-Context Mention Resolution Benchmark for LLMs
https://github.com/kentonl/e2e-coref
공식 코드https://github.com/kiankd/events
공식 코드https://github.com/klimzaporojets/DWIE
공식 코드DWIE: an entity-centric dataset for multi-task document-level information extraction
https://github.com/klimzaporojets/consistent-el
공식 코드https://github.com/klimzaporojets/e2e-kb-ie
공식 코드https://github.com/kosciukiewicz/similarity_based_memory_re
공식 코드Similarity-based Memory Enhanced Joint Entity and Relation Extraction
https://github.com/kumar-shridhar/longtonotes
공식 코드https://github.com/laituan245/eventcoref
공식 코드https://github.com/lavis-nlp/jerex
공식 코드An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learning
https://github.com/lmmapplication/rakg
공식 코드RAKG:Document-level Retrieval Augmented Knowledge Graph Construction
https://github.com/lucyyyw/ambicoref
공식 코드AmbiCoref: Evaluating Human and Model Sensitivity to Ambiguous Coreference
https://github.com/luyaojie/E3C
공식 코드https://github.com/lxucs/coref-hoi
공식 코드Revealing the Myth of Higher-Order Inference in Coreference Resolution
https://github.com/lyutyuh/asp
공식 코드https://github.com/lyutyuh/structured-span-selector
공식 코드https://github.com/mandarjoshi90/coref
공식 코드https://github.com/mbzuai-nlp/lamini-lm
공식 코드LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
https://github.com/mgrenander/sentence-incremental-coref
공식 코드https://github.com/microsoft/DeBERTa
공식 코드https://github.com/mpoemsl/kitmus
공식 코드https://github.com/namisan/mt-dnn
공식 코드https://github.com/nle18/coref-llms
공식 코드https://github.com/nlp-chula/thai-coref
공식 코드https://github.com/ns-moosavi/coval
공식 코드https://github.com/ns-moosavi/epm
공식 코드Using Linguistic Features to Improve the Generalization Capability of Neural Coreference Resolvers
https://github.com/nupoorgandhi/data-eff-coref
공식 코드Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution
https://github.com/nupoorgandhi/i2b2-coref-public
공식 코드Improving Span Representation for Domain-adapted Coreference Resolution
https://github.com/nurakib/event-question-answering
공식 코드Asking and Answering Questions to Extract Event-Argument Structures
https://github.com/ondfa/coref-multiling
공식 코드Exploring Multiple Strategies to Improve Multilingual Coreference Resolution in CorefUD
https://github.com/openai/gpt-3
공식 코드https://github.com/paragdakle/emailcoref
공식 코드CEREC: A Corpus for Entity Resolution in Email Conversations
https://github.com/prafulla77/TAC-KBP-2017-Participation
공식 코드TAMU at KBP 2017: Event Nugget Detection and Coreference Resolution
https://github.com/ptrichel/How-Reasonable-are-Common-Sense-Reasoning-Tasks
공식 코드https://github.com/rahular/ellipsis-baselines
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.