https://github.com/ariecattan/SciCo
공식 코드SciCo: Hierarchical Cross-Document Coreference for Scientific Concepts
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/ariecattan/champ
공식 코드CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies
https://github.com/ariecattan/coref
공식 코드Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling
https://github.com/arthurbra/stm-coref
공식 코드Coreference Resolution in Research Papers from Multiple Domains
https://github.com/aviclu/CD-LM
공식 코드https://github.com/aviclu/cdlm
공식 코드https://github.com/awesomecoref/prompt-coref
공식 코드https://github.com/belindal/discrete-active-learning-coref
공식 코드Active Learning for Coreference Resolution using Discrete Annotation
https://github.com/bigscience-workshop/xmtf
공식 코드https://github.com/boyuanzheng010/mmc
공식 코드https://github.com/cgraywang/deepstruct
공식 코드DeepStruct: Pretraining of Language Models for Structure Prediction
https://github.com/clarkkev/deep-coref
공식 코드Improving Coreference Resolution by Learning Entity-Level Distributed Representations
https://github.com/compnet/splice
공식 코드The Role of Natural Language Processing Tasks in Automatic Literary Character Network Construction
https://github.com/cooper12121/cles
공식 코드Harvesting Events from Multiple Sources: Towards a Cross-Document Event Extraction Paradigm
https://github.com/cooper12121/die-ec
공식 코드https://github.com/csu-signal/llama_cdcr
공식 코드Okay, Let's Do This! Modeling Event Coreference with Generated Rationales and Knowledge Distillation
https://github.com/csu-signal/multimodal-coreference
공식 코드https://github.com/dair-iitd/mokb6
공식 코드mOKB6: A Multilingual Open Knowledge Base Completion Benchmark
https://github.com/danield21/rationale4cdecr
공식 코드https://github.com/dbamman/litbank
공식 코드https://github.com/dbamman/lrec2020-coref
공식 코드https://github.com/deadcardassian/poscorefimpact
공식 코드https://github.com/dlion168/Listen-and-Speak-Fairly
공식 코드Listen and Speak Fairly: A Study on Semantic Gender Bias in Speech Integrated Large Language Models
https://github.com/egilron/elsa-introduction
공식 코드Entity-Level Sentiment Analysis (ELSA): An exploratory task survey
https://github.com/eleutherai/gpt-neox
공식 코드Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
https://github.com/eleutherai/pythia
공식 코드Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
https://github.com/emerging-welfare/ecr4-contentious-politics
공식 코드Event Coreference Resolution for Contentious Politics Events
https://github.com/emorynlp/elit
공식 코드https://github.com/facebookresearch/SpanBERT
공식 코드SpanBERT: Improving Pre-training by Representing and Predicting Spans
https://github.com/fantabulous-j/coref-constituent-graph
공식 코드https://github.com/forest-snow/incremental-coref
공식 코드Adapting Coreference Resolution Models through Active Learning
https://github.com/forrestdavis/ImplicitCausality
공식 코드Discourse structure interacts with reference but not syntax in neural language models
https://github.com/gabrielStanovsky/yall
공식 코드Yall should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts
https://github.com/gnkitaa/ezcoref
공식 코드ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution
https://github.com/google-research-datasets/contrack
공식 코드A Unified Approach to Entity-Centric Context Tracking in Social Conversations
https://github.com/google-research/bert
공식 코드BERT: 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.