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Slot Filling

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하위 태스크: 2
평가표: 14
보존된 평가 기록: 110

The goal of Slot Filling is to identify from a running dialog different slots, which correspond to different parameters of the user’s query. For instance, when a user queries for nearby restaurants, key slots for location and preferred food are required for a dialog system to retrieve the appropriate information. Thus, the main challenge in the slot-filling task is to extract the target entity.

Source: Real-time On-Demand Crowd-powered Entity Extraction

Image credit: Robust Retrieval Augmented Generation for Zero-shot Slot Filling

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/robvanderg/xsid

공식 코드

From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding

https://github.com/AaronTengDeChuan/MLWA-Chinese-SLU

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Injecting Word Information with Multi-Level Word Adapter for Chinese Spoken Language Understanding

https://github.com/Adaxry/CM-Net

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CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding

https://github.com/Ayushk4/extract_covid_entity

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Leveraging Event Specific and Chunk Span features to Extract COVID Events from tweets

https://github.com/ChestnutWYN/ACL2021-Novel-Slot-Detection

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Novel Slot Detection: A Benchmark for Discovering Unknown Slot Types in the Task-Oriented Dialogue System

https://github.com/DigitalDigger/MeTooMaastrichtChatbot

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#MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment

https://github.com/F2-Song/PromptSLU

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A Unified Framework for Multi-intent Spoken Language Understanding with prompting

https://github.com/IBM/retrieve-write-slot-filling

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Zero-shot Slot Filling with DPR and RAG

https://github.com/Kaleidophon/deep-significance

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From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding

https://github.com/LeePleased/StackPropagation-SLU

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A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding

https://github.com/Liang-Qiu/is13

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Recurrent Neural Networks with Pre-trained Language Model Embedding for Slot Filling Task

https://github.com/LooperXX/AGIF

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AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling

https://github.com/Makbari1997/Persian-Atis

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A Persian Benchmark for Joint Intent Detection and Slot Filling

https://github.com/NVIDIA/NeMo

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Efficient Sequence Transduction by Jointly Predicting Tokens and Durations

https://github.com/PolyAI-LDN/task-specific-datasets

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Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations

https://github.com/PragmaticsLab/CodeSwitchingAdversarial

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Call Larisa Ivanovna: Code-Switching Fools Multilingual NLU Models

https://github.com/Sanyuan-Chen/C2C-DA

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C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot Filling

https://github.com/TRUMANCFY/SLIM

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SLIM: Explicit Slot-Intent Mapping with BERT for Joint Multi-Intent Detection and Slot Filling

https://github.com/ToLightUpTheSky/ParsingDST

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Semantic Parsing by Large Language Models for Intricate Updating Strategies of Zero-Shot Dialogue State Tracking

https://github.com/VinAIResearch/JointIDSF

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Intent Detection and Slot Filling for Vietnamese

https://github.com/ZovanZhou/MLRN

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Multi-grained Label Refinement Network with Dependency Structures for Joint Intent Detection and Slot Filling

https://github.com/adlnlp/tri-nlu

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Tri-level Joint Natural Language Understanding for Multi-turn Conversational Datasets

https://github.com/aetherprior/multilingual-sentence-boundary-detection

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Punctuation Restoration for Singaporean Spoken Languages: English, Malay, and Mandarin

https://github.com/ago3/plead

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Explainable Abuse Detection as Intent Classification and Slot Filling

https://github.com/ai-agi/hicl

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HierarchicalContrast: A Coarse-to-Fine Contrastive Learning Framework for Cross-Domain Zero-Shot Slot Filling

https://github.com/ala-na/media_benchmark_intent_annotations

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New Semantic Task for the French Spoken Language Understanding MEDIA Benchmark

https://github.com/alexa/massive

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MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

https://github.com/algoprog/syntod

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Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Models

https://github.com/amazon-research/stil-mbart-multiatis

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STIL -- Simultaneous Slot Filling, Translation, Intent Classification, and Language Identification: Initial Results using mBART on MultiATIS++

https://github.com/anhtunguyen98/bislu

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Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation

https://github.com/anthonywchen/AmbER-Sets

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Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP

https://github.com/blester125/iobes

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iobes: A Library for Span-Level Processing

https://github.com/boschresearch/sofc-exp_textmining_resources

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The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain

https://github.com/briansidp/espnet

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End-to-end Spoken Language Understanding with Tree-constrained Pointer Generator

https://github.com/bytedance/salmonn

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SALMONN: Towards Generic Hearing Abilities for Large Language Models

https://github.com/ccied/ugforum-analysis

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Identifying Products in Online Cybercrime Marketplaces: A Dataset for Fine-grained Domain Adaptation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.