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Response Generation

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하위 태스크: 0
평가표: 3
보존된 평가 기록: 10

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/snakeztc/NeuralDialog-LAED

공식 코드

Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation

https://github.com/snumprlab/SRT

공식 코드

ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO

https://github.com/snumprlab/isr-dpo

공식 코드

ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO

https://github.com/sogang-isds/TOATOD

공식 코드

Task-Optimized Adapters for an End-to-End Task-Oriented Dialogue System

https://github.com/songhaoyu/BoB

공식 코드

BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data

https://github.com/sreyan88/vdgd

공식 코드

Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs

https://github.com/srsohn/tod-flow

공식 코드

TOD-Flow: Modeling the Structure of Task-Oriented Dialogues

https://github.com/starrYYxuan/IPS

공식 코드

Fine-grained Conversational Decoding via Isotropic and Proximal Search

https://github.com/starsuzi/videorag

공식 코드

VideoRAG: Retrieval-Augmented Generation over Video Corpus

https://github.com/stevekgyang/vad-vae

공식 코드

Disentangled Variational Autoencoder for Emotion Recognition in Conversations

https://github.com/suletekkesinoglu/xai_llm_rag

공식 코드

From Feature Importance to Natural Language Explanations Using LLMs with RAG

https://github.com/sunnweiwei/genks

공식 코드

Generative Knowledge Selection for Knowledge-Grounded Dialogues

https://github.com/suntea233/duetsim

공식 코드

DuetSim: Building User Simulator with Dual Large Language Models for Task-Oriented Dialogues

https://github.com/suvodipdey/bok

공식 코드

BoK: Introducing Bag-of-Keywords Loss for Interpretable Dialogue Response Generation

https://github.com/suvodipdey/dialogen

공식 코드

DialoGen: Generalized Long-Range Context Representation for Dialogue Systems

https://github.com/tamhome/tam_dynamic_map

공식 코드

Unified Understanding of Environment, Task, and Human for Human-Robot Interaction in Real-World Environments

https://github.com/teigenzhang/escot

공식 코드

ESCoT: Towards Interpretable Emotional Support Dialogue Systems

https://github.com/thu-coai/reverse_generation

공식 코드

Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation

https://github.com/tigerwww-git/rt-kgd

공식 코드

RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation

https://github.com/tomiinek/aargh

공식 코드

AARGH! End-to-end Retrieval-Generation for Task-Oriented Dialog

https://github.com/tommytyc/rsvp

공식 코드

RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training

https://github.com/truthless11/CR-Walker

공식 코드

CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendation

https://github.com/tunib-ai/parallelformers

공식 코드

Few-Shot Bot: Prompt-Based Learning for Dialogue Systems

https://github.com/uic-nlp-lab/virtualcoachdata

공식 코드

Towards Enhancing Health Coaching Dialogue in Low-Resource Settings

https://github.com/ukplab/arxiv2022-argscichat

공식 코드

ArgSciChat: A Dataset for Argumentative Dialogues on Scientific Papers

https://github.com/ukplab/arxiv2024-attribute-or-abstain

공식 코드

Attribute or Abstain: Large Language Models as Long Document Assistants

https://github.com/ukplab/dior-cvae

공식 코드

Dior-CVAE: Pre-trained Language Models and Diffusion Priors for Variational Dialog Generation

https://github.com/ukplab/emnlp2023-learning-from-free-text-human-feedback

공식 코드

Learning From Free-Text Human Feedback -- Collect New Datasets Or Extend Existing Ones?

https://github.com/ulrs0/MA-PO

공식 코드

The Fellowship of the LLMs: Multi-Agent Workflows for Synthetic Preference Optimization Dataset Generation

https://github.com/umanlp/RedditBias

공식 코드

RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models

https://github.com/vectorinstitute/naa

공식 코드

Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support

https://github.com/wangjs9/care-master

공식 코드

CARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generation

https://github.com/wangyufeng-empty/ctsm

공식 코드

CTSM: Combining Trait and State Emotions for Empathetic Response Model

https://github.com/wenhuchen/HDSA-Dialog

공식 코드

Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention

https://github.com/whatissimondoing/cog-bart

공식 코드

Contrast and Generation Make BART a Good Dialogue Emotion Recognizer

https://github.com/williamstoto/cgdialog

공식 코드

Less is More: Mitigate Spurious Correlations for Open-Domain Dialogue Response Generation Models by Causal Discovery

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