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Chunking
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Chunking, also known as shallow parsing, identifies continuous spans of tokens that form syntactic units such as noun phrases or verb phrases.
Example:
| Vinken | , | 61 | years | old |
|---|---|---|---|---|
| B-NLP | I-NP | I-NP | I-NP | I-NP |
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Adaxry/GCDT
공식 코드GCDT: A Global Context Enhanced Deep Transition Architecture for Sequence Labeling
https://github.com/Alibaba-NLP/ACE
공식 코드Automated Concatenation of Embeddings for Structured Prediction
https://github.com/Alibaba-NLP/AIN
공식 코드AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network
https://github.com/Alibaba-NLP/CoFE-RAG
공식 코드https://github.com/HongyuGong/RCM-Question-Answering
공식 코드Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension
https://github.com/HornHehhf/TAWT
공식 코드https://github.com/IAAR-Shanghai/Meta-Chunking
공식 코드Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception
https://github.com/KNOT-FIT-BUT/QBEK
공식 코드https://github.com/LeePleased/LeftmostSeg
공식 코드Neural Sequence Segmentation as Determining the Leftmost Segments
https://github.com/Nouf-Alabbasi/oKUmura_AI_Telecom_challenge
공식 코드Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards
https://github.com/PKUDigitalHealth/KidneyTalk-open
공식 코드https://github.com/Physical-Intelligence/real-time-chunking-kinetix
공식 코드https://github.com/RezzFayyazi/ProveRAG
공식 코드ProveRAG: Provenance-Driven Vulnerability Analysis with Automated Retrieval-Augmented LLMs
https://github.com/SLQu/CmnRec
공식 코드CmnRec: Sequential Recommendations with Chunk-accelerated Memory Network
https://github.com/UKPLab/emnlp2017-bilstm-cnn-crf
공식 코드Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks
https://github.com/Vprashant/s2-chunking-lib
공식 코드https://github.com/YuejiangLIU/bid_diffusion
공식 코드Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
https://github.com/ZGChung/Mix-of-Granularity
공식 코드Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation
https://github.com/aakhundov/sequence-labeling
공식 코드https://github.com/aatlantise/punc-rest-improves
공식 코드Punctuation Restoration Improves Structure Understanding Without Supervision
https://github.com/abdelfattah-lab/attamba
공식 코드https://github.com/abhibambhaniya/genz-llm-analyzer
공식 코드Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models
https://github.com/aditya-ramesh-10/chunktd
공식 코드Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
https://github.com/ai-ku/wvec
공식 코드Substitute Based SCODE Word Embeddings in Supervised NLP Tasks
https://github.com/amal994/experiential-explanations-rl
공식 코드https://github.com/apple/ml-dataset-decomposition
공식 코드Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum
https://github.com/asappresearch/scale-score
공식 코드Fast and Accurate Factual Inconsistency Detection Over Long Documents
https://github.com/bplank/coling2016ks
공식 코드https://github.com/daviddongkc/chunk_oie
공식 코드https://github.com/deadcardassian/poscorefimpact
공식 코드https://github.com/disi-unibo-nlp/rag-when-how-chunk
공식 코드Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generation
https://github.com/dmlguq456/SepReformer
공식 코드Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation
https://github.com/dorringel/SWVM
공식 코드https://github.com/ecnu-text-computing/dcs
공식 코드https://github.com/filemon11/discoparset-supertag
공식 코드Integrating Supertag Features into Neural Discontinuous Constituent Parsing
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