https://github.com/ndaheim/faithful-dialogue
공식 코드Elastic Weight Removal for Faithful and Abstractive Dialogue Generation
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/nealcly/ke-blender
공식 코드Knowledge Enhanced Fine-Tuning for Better Handling Unseen Entities in Dialogue Generation
https://github.com/neukg/kat-tslf
공식 코드A Three-Stage Learning Framework for Low-Resource Knowledge-Grounded Dialogue Generation
https://github.com/nii-yamagishilab/AfriHuBERT
공식 코드AfriHuBERT: A self-supervised speech representation model for African languages
https://github.com/nikitacs16/xlift_dst
공식 코드Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking
https://github.com/nlp-rl/semtextuallogue-loss
공식 코드https://github.com/nlper27149/luna-dst
공식 코드LUNA: Learning Slot-Turn Alignment for Dialogue State Tracking
https://github.com/nlpxucan/ZRKGC
공식 코드https://github.com/nlpyang/geval
공식 코드G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
https://github.com/nmrksic/attract-repel
공식 코드https://github.com/nmrksic/counter-fitting
공식 코드https://github.com/nmrksic/neural-belief-tracker
공식 코드https://github.com/nob0/crs-breakdown-detection
공식 코드Identifying Breakdowns in Conversational Recommender Systems using User Simulation
https://github.com/ntunlplab/fecs
공식 코드https://github.com/ntwalker/graphwoz
공식 코드GraphWOZ: Dialogue Management with Conversational Knowledge Graphs
https://github.com/nu-dialogue/jmultiwoz
공식 코드JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset
https://github.com/nu-dialogue/post-processing-networks
공식 코드https://github.com/nuochenpku/harry-potter-dialogue-dataset
공식 코드https://github.com/nvidia/nemo-guardrails
공식 코드NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Rails
https://github.com/observeai-research/nli-fsl
공식 코드Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection
https://github.com/orange-opensource/olisia-dstc11
공식 코드https://github.com/osu-nlp-group/tacobot
공식 코드Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue System
https://github.com/oswaldoludwig/Adversarial-Learning-for-Generative-Conversational-Agents
공식 코드End-to-end Adversarial Learning for Generative Conversational Agents
https://github.com/oswaldoludwig/Seq2seq-Chatbot-for-Keras
공식 코드End-to-end Adversarial Learning for Generative Conversational Agents
https://github.com/pascalson/causaldialogue
공식 코드CausalDialogue: Modeling Utterance-level Causality in Conversations
https://github.com/patrick-tssn/VSTAR
공식 코드https://github.com/pgurunath/confusion2vec_2.0
공식 코드Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with Subwords
https://github.com/pgurunath/slu_confusion2vec
공식 코드https://github.com/phellonchen/DMRM
공식 코드DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog
https://github.com/phlippe/P2_Net
공식 코드Diversifying Task-oriented Dialogue Response Generation with Prototype Guided Paraphrasing
https://github.com/ppartha03/Dialogue-Compositionality-of-Generative-Transformer
공식 코드On Task-Level Dialogue Composition of Generative Transformer Model
https://github.com/prakharguptaz/EDGE-exemplars
공식 코드https://github.com/prakharguptaz/Instructdial
공식 코드InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
https://github.com/pswietojanski/slurp
공식 코드https://github.com/pzelasko/daseg
공식 코드https://github.com/qtli/EmpDG
공식 코드EmpDG: Multiresolution Interactive Empathetic Dialogue Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.