https://github.com/iwangjian/trip
공식 코드Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue
Papers with Code 아카이브
Dialogue
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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Dialogue is notoriously hard to evaluate. Past approaches have used human evaluation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jacklxc/ms.wow
공식 코드A Knowledge Plug-and-Play Test Bed for Open-domain Dialogue Generation
https://github.com/jasonwu0731/GLMP
공식 코드Global-to-local Memory Pointer Networks for Task-Oriented Dialogue
https://github.com/jasonwu0731/ToD-BERT
공식 코드TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue
https://github.com/jasonwu0731/trade-dst
공식 코드Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
https://github.com/jcyk/skeleton-to-response
공식 코드Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory
https://github.com/jeff-sue/urt
공식 코드Unsupervised Mutual Learning of Dialogue Discourse Parsing and Topic Segmentation
https://github.com/jefflai108/Semi-Supervsied-Spoken-Language-Understanding-PyTorch
공식 코드https://github.com/jennycs0830/confidence_score_dst
공식 코드https://github.com/jensen-w/retqa
공식 코드RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector
https://github.com/jensenw1/RETQA
공식 코드RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector
https://github.com/jeremyleiliu/xlingudial
공식 코드https://github.com/jfzhouyoo/case
공식 코드CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation
https://github.com/jgkimi/Decay-Function-Free-Time-Aware
공식 코드https://github.com/jiasenlu/HieCoAttenVQA
공식 코드Hierarchical Question-Image Co-Attention for Visual Question Answering
https://github.com/jiasenlu/visDial.pytorch
공식 코드https://github.com/jichangzhen/CCN
공식 코드https://github.com/jiho283/simulator
공식 코드https://github.com/jihyunlee1/e2e-dst
공식 코드Exploring the Viability of Synthetic Audio Data for Audio-Based Dialogue State Tracking
https://github.com/jin8/adlm
공식 코드Language Detoxification with Attribute-Discriminative Latent Space
https://github.com/jind11/rede
공식 코드Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue Systems
https://github.com/jisilverh/psydial
공식 코드PSYDIAL: Personality-based Synthetic Dialogue Generation using Large Language Models
https://github.com/jkkummerfeld/irc-disentanglement
공식 코드https://github.com/jlab-nlp/nc_latent_tod
공식 코드Unsupervised End-to-End Task-Oriented Dialogue with LLMs: The Power of the Noisy Channel
https://github.com/jlab-nlp/refpydst
공식 코드Diverse Retrieval-Augmented In-Context Learning for Dialogue State Tracking
https://github.com/jokieleung/ntrd
공식 코드https://github.com/jqtangust/hawk
공식 코드https://github.com/jshin49/ds2
공식 코드https://github.com/julianser/Ubuntu-Multiresolution-Tools
공식 코드Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation
https://github.com/justtherightsize/empo
공식 코드EmPO: Emotion Grounding for Empathetic Response Generation through Preference Optimization
https://github.com/k2-fsa/ZipVoice
공식 코드ZipVoice-Dialog: Non-Autoregressive Spoken Dialogue Generation with Flow Matching
https://github.com/kaishxu/DFMed
공식 코드https://github.com/kangbrilliant/DCA-Net
공식 코드A Co-Interactive Transformer for Joint Slot Filling and Intent Detection
https://github.com/kaniblu/vhda
공식 코드Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation
https://github.com/kentchang/dramatic-conversation-disentanglement
공식 코드https://github.com/kepei1106/decompeval
공식 코드DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question Answering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.