Papers with Code 아카이브
Dialogue
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/qtli/kemp
공식 코드https://github.com/qywu/memformers
공식 코드Stateful Memory-Augmented Transformers for Efficient Dialogue Modeling
https://github.com/qzx7/mindthetime
공식 코드Mind the Gap Between Conversations for Improved Long-Term Dialogue Generation
https://github.com/r9729104234/Emotion-Aware-Transformer-Encoder-for-Empathetic-Dialogue-Generation
공식 코드Emotion-Aware Transformer Encoder for Empathetic Dialogue Generation
https://github.com/radi-cho/rstod
공식 코드Efficient Task-Oriented Dialogue Systems with Response Selection as an Auxiliary Task
https://github.com/rafaelhferreira/mtad_cta
공식 코드Multi-trait User Simulation with Adaptive Decoding for Conversational Task Assistants
https://github.com/rasahq/tod-in-context-learning
공식 코드https://github.com/rashad101/dialokg
공식 코드DialoKG: Knowledge-Structure Aware Task-Oriented Dialogue Generation
https://github.com/ravoxsg/efficient_unified_crs
공식 코드Parameter-Efficient Conversational Recommender System as a Language Processing Task
https://github.com/reecall/graphtod
공식 코드https://github.com/renll/ComerNet
공식 코드Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation
https://github.com/rikdz/GraphWriter
공식 코드Text Generation from Knowledge Graphs with Graph Transformers
https://github.com/rita-nlp/italic
공식 코드https://github.com/rowitzou/cg-nar
공식 코드https://github.com/ruanvdmerwe/triplet-entropy-loss
공식 코드Triplet Entropy Loss: Improving The Generalisation of Short Speech Language Identification Systems
https://github.com/ruc-gsai/yulan-rec
공식 코드User Behavior Simulation with Large Language Model based Agents
https://github.com/ruckbreasoning/glm-dialog
공식 코드GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
https://github.com/ruizhaogit/GuessWhat-TemperedPolicyGradient
공식 코드Learning Goal-Oriented Visual Dialog via Tempered Policy Gradient
https://github.com/ruizhaogit/MNIST-GuessNumber
공식 코드Efficient Dialog Policy Learning via Positive Memory Retention
https://github.com/ruizhaogit/PositiveMemoryRetention
공식 코드Efficient Dialog Policy Learning via Positive Memory Retention
https://github.com/russellliu0/rad
공식 코드https://github.com/ryanzhumich/editsql
공식 코드Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions
https://github.com/ryota-komatsu/speaker_disentangled_hubert
공식 코드Self-Supervised Syllable Discovery Based on Speaker-Disentangled HuBERT
https://github.com/s6fikass/Chatbot_KVNN
공식 코드Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task Learning
https://github.com/saketdingliwal/Few-Shot-DST
공식 코드https://github.com/salesforce/CASPI
공식 코드Causal-aware Safe Policy Improvement for Task-oriented dialogue
https://github.com/salesforce/DNNC-few-shot-intent
공식 코드Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
https://github.com/salesforce/VD-BERT
공식 코드https://github.com/salesforce/botsim
공식 코드BotSIM: An End-to-End Bot Simulation Toolkit for Commercial Task-Oriented Dialog Systems
https://github.com/salesforce/coco-dst
공식 코드CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers
https://github.com/salesforce/converse
공식 코드Converse: A Tree-Based Modular Task-Oriented Dialogue System
https://github.com/salesforce/glad
공식 코드https://github.com/salesforce/lavis
공식 코드https://github.com/salesforce/simpletod
공식 코드https://github.com/samsung/mt-llm-nlu
공식 코드Large Language Models for Expansion of Spoken Language Understanding Systems to New Languages
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.