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Response Generation
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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/informagi/laps
공식 코드https://github.com/inimah/metric-preference-checklist
공식 코드NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
https://github.com/isi-nlp/recap
공식 코드RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation
https://github.com/jacklxc/ms.wow
공식 코드A Knowledge Plug-and-Play Test Bed for Open-domain Dialogue Generation
https://github.com/jacksonwuxs/interpret_instruction_tuning_llms
공식 코드https://github.com/jasonyux/krls
공식 코드https://github.com/jcyk/skeleton-to-response
공식 코드Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory
https://github.com/jfzhouyoo/case
공식 코드CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation
https://github.com/jiezouir/pscon
공식 코드https://github.com/jing-qian/A-Benchmark-Dataset-for-Learning-to-Intervene-in-Online-Hate-Speech
공식 코드A Benchmark Dataset for Learning to Intervene in Online Hate Speech
https://github.com/jliu-v/CoMAC
공식 코드https://github.com/jqk09a/CoRe-dialogue-filtering
공식 코드Filtering Noisy Dialogue Corpora by Connectivity and Content Relatedness
https://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/kanak8278/dialogkperm
공식 코드https://github.com/kaniblu/vhda
공식 코드Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation
https://github.com/kyle8581/dialoguecot
공식 코드Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents
https://github.com/lackel/agla
공식 코드https://github.com/lddsdu/VRBot
공식 코드Semi-Supervised Variational Reasoning for Medical Dialogue Generation
https://github.com/leezekun/directional-stimulus-prompting
공식 코드Guiding Large Language Models via Directional Stimulus Prompting
https://github.com/lemonsis/ctrlstruct
공식 코드CTRLStruct: Dialogue Structure Learning for Open-Domain Response Generation
https://github.com/lemuria-wchen/DialogVED
공식 코드DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation
https://github.com/leolee99/ld-agent
공식 코드Hello Again! LLM-powered Personalized Agent for Long-term Dialogue
https://github.com/liangzid/TEMP
공식 코드Healing Unsafe Dialogue Responses with Weak Supervision Signals
https://github.com/lingzhi-wang/kgaunlearn
공식 코드KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment
https://github.com/liyucheng09/selective_context
공식 코드Compressing Context to Enhance Inference Efficiency of Large Language Models
https://github.com/lorashen/auto-slurp
공식 코드Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant
https://github.com/lpq29743/cedual
공식 코드Modeling Content-Emotion Duality via Disentanglement for Empathetic Conversation
https://github.com/lwgkzl/MedDG
공식 코드MedDG: An Entity-Centric Medical Consultation Dataset for Entity-Aware Medical Dialogue Generation
https://github.com/lxchtan/DSTC9-Track1
공식 코드https://github.com/lxchtan/hetermpc
공식 코드HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations
https://github.com/lzy-the-boys/miracle
공식 코드https://github.com/manishemirani/void_in_language_models
공식 코드https://github.com/marcoguerini/vermouth
공식 코드https://github.com/maszhongming/unieval
공식 코드Towards a Unified Multi-Dimensional Evaluator for Text Generation
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