Dialogue State Tracking
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Dialogue state tacking consists of determining at each turn of a dialogue the full representation of what the user wants at that point in the dialogue, which contains a goal constraint, a set of requested slots, and the user's dialogue act.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/milmor/GPT
https://github.com/mindspore-ai/models/blob/master/research/nlp/gpt2
https://github.com/minimaxir/gpt-2-simple
https://github.com/openai/gpt-2
https://github.com/qbxlvnf11/MultiWOZ2.1-Parser
https://github.com/ramanakshay/nanogpt
https://github.com/renll/StateNet
https://github.com/ryanzhumich/sparc_atis_pytorch
https://github.com/s-nlp/sgdd-tst
Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset
https://github.com/servicenow/picard
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
https://github.com/shizhediao/SEDST3
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
https://github.com/skoltech-nlp/sgdd-tst
Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset
https://github.com/sogang-isds/TOATOD
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
https://github.com/stanford-oval/genienlp
Contextual Semantic Parsing for Multilingual Task-Oriented Dialogues
https://github.com/stanford-oval/schema2qa
A Few-Shot Semantic Parser for Wizard-of-Oz Dialogues with the Precise ThingTalk Representation
https://github.com/varun-suresh/experiments-with-gpt2
https://github.com/vzhong/gazp
Grounded Adaptation for Zero-shot Executable Semantic Parsing
https://github.com/xubuvd/guesswhat
https://github.com/yangyucheng000/Paper-3/tree/main/acm-mm-2023-picr-master
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.