https://github.com/lxchtan/tegtok
공식 코드TegTok: Augmenting Text Generation via Task-specific and Open-world Knowledge
Papers with Code 아카이브
Dialogue
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 21
- 평가표
- 1
- 보존된 평가 기록
- 1
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/lyy1994/plm_as_kb
공식 코드Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation
https://github.com/lzy-the-boys/miracle
공식 코드https://github.com/m3hrdadfi/mogpt
공식 코드An Empirical Study of Multitask Learning to Improve Open Domain Dialogue Systems
https://github.com/mailong25/rts2s-dg
공식 코드https://github.com/mainlp/dialect-tod-robustness
공식 코드Exploring the Robustness of Task-oriented Dialogue Systems for Colloquial German Varieties
https://github.com/manga-uofa/eqhard-em
공식 코드An Equal-Size Hard EM Algorithm for Diverse Dialogue Generation
https://github.com/manuelgentile/inforob
공식 코드A Storytelling Robot managing Persuasive and Ethical Stances via ACT-R: an Exploratory Study
https://github.com/marekkubis/bteval
공식 코드https://github.com/maxlchen/controllable-mixed-initiative-dialogue-generation
공식 코드Controllable Mixed-Initiative Dialogue Generation through Prompting
https://github.com/maxxkia/g-ssl-crf
공식 코드https://github.com/mcogswell/dialog_without_dialog
공식 코드Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data
https://github.com/mct10/repcodec
공식 코드RepCodec: A Speech Representation Codec for Speech Tokenization
https://github.com/meow-e/usimagent
공식 코드USimAgent: Large Language Models for Simulating Search Users
https://github.com/michael-wzhu/PromptCBLUE
공식 코드PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domain
https://github.com/microsoft/dialoglm
공식 코드DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization
https://github.com/miguel-kjh/Improving-Dialogue-Management
공식 코드https://github.com/mikezhang95/HDNO
공식 코드https://github.com/mirah-official/empathetic-chatbot-asem
공식 코드ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion Modeling
https://github.com/misonsky/Amdg
공식 코드A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation
https://github.com/miulab/cuda-dst
공식 코드Controllable User Dialogue Act Augmentation for Dialogue State Tracking
https://github.com/miulab/salesbot
공식 코드SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues
https://github.com/miulab/spokencse
공식 코드Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding
https://github.com/mohit2b/ecosage
공식 코드An EcoSage Assistant: Towards Building A Multimodal Plant Care Dialogue Assistant
https://github.com/momohuang/FlowQA
공식 코드FlowQA: Grasping Flow in History for Conversational Machine Comprehension
https://github.com/moncefbenaicha/spoken-ner
공식 코드Leveraging Cross-Lingual Transfer Learning in Spoken Named Entity Recognition Systems
https://github.com/moore3930/SlotRefine
공식 코드SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling
https://github.com/mozerwang/demo
공식 코드DEMO: Reframing Dialogue Interaction with Fine-grained Element Modeling
https://github.com/mrflogs/LoRA-Pro
공식 코드https://github.com/mtkresearch/taste-spokenlm
공식 코드TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modeling
https://github.com/mubtasimahasan/dm-codec
공식 코드DM-Codec: Distilling Multimodal Representations for Speech Tokenization
https://github.com/mutonix/refgpt
공식 코드https://github.com/muyeby/AMR-Dialogue
공식 코드https://github.com/myt517/kcod
공식 코드https://github.com/naver-ai/neuralwoz
공식 코드NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-Based Simulation
https://github.com/naver/aqm-plus
공식 코드Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.