https://github.com/willyhc22/instructtods
공식 코드InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systems
Papers with Code 아카이브
Response Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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A task where an agent should play the $DE$ role and generate a text to respond to a $P$ message.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wlr737/emnlp2022-seek
공식 코드Empathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection
https://github.com/wu0409/antidote
공식 코드https://github.com/wyu-du/self-training-dialogue-generation
공식 코드Self-training with Two-phase Self-augmentation for Few-shot Dialogue Generation
https://github.com/xcfcode/PLM_annotator
공식 코드Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization
https://github.com/xl2248/csa-nct
공식 코드Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
https://github.com/xmudm/guide-align
공식 코드Ensuring Safe and High-Quality Outputs: A Guideline Library Approach for Language Models
https://github.com/xunguangwang/instructta
공식 코드InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models
https://github.com/yingtaomj/Reasoning-in-Dialog
공식 코드Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension
https://github.com/yiweijiang2015/cookdial
공식 코드CookDial: A dataset for task-oriented dialogs grounded in procedural documents
https://github.com/yizhen20133868/Retriever-Dialogue
공식 코드Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever
https://github.com/yizhen20133868/ci-tod
공식 코드https://github.com/yjeugenia/maferw
공식 코드MaFeRw: Query Rewriting with Multi-Aspect Feedbacks for Retrieval-Augmented Large Language Models
https://github.com/ynandwan/pmi-faith
공식 코드https://github.com/yuboxie/meed2
공식 코드https://github.com/yunhaoli1995/MAMD-TOD
공식 코드Retrieve & Memorize: Dialog Policy Learning with Multi-Action Memory
https://github.com/yunqing-me/attackvlm
공식 코드On Evaluating Adversarial Robustness of Large Vision-Language Models
https://github.com/yuyaozhangqaq/query_compiler
공식 코드https://github.com/yyy-apple/sys-nl-feedback
공식 코드https://github.com/zenggo/affective-decoding-4-empathetic-dialog
공식 코드https://github.com/zhangbo-nlp/zrigf
공식 코드ZRIGF: An Innovative Multimodal Framework for Zero-Resource Image-Grounded Dialogue Generation
https://github.com/zhangce01/degf
공식 코드https://github.com/zhanghainan/ReCoSa
공식 코드ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
https://github.com/zhanhl316/flowchart-dialogue-with-da
공식 코드https://github.com/zhaoxlpku/KnowledGPT
공식 코드Knowledge-Grounded Dialogue Generation with Pre-trained Language Models
https://github.com/zhengxiangshi/lexicalentrainment
공식 코드https://github.com/zhiyuanpeng/eloq
공식 코드ELOQ: Resources for Enhancing LLM Detection of Out-of-Scope Questions
https://github.com/zhouzhouyang520/empatheticdialoguegeneration_escm
공식 코드Exploiting Emotion-Semantic Correlations for Empathetic Response Generation
https://github.com/zhouzhouyang520/iamm
공식 코드An Iterative Associative Memory Model for Empathetic Response Generation
https://github.com/ziweiji/Internal_States_Reveal_Hallucination
공식 코드LLM Internal States Reveal Hallucination Risk Faced With a Query
https://github.com/zlinao/MinTL
공식 코드MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems
https://github.com/zlinao/Variational-Transformer
공식 코드https://github.com/zxd-octopus/ECR
공식 코드https://huggingface.co/datasets/SoftMINER-Group/TechHazardQA
공식 코드https://github.com/2023-MindSpore-1/ms-code-154
https://github.com/23LuZ/the-Evaluation-of-ChitChat-System
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.