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Open-Domain Dialog
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MEDAL: A Framework for Benchmarking LLMs as Multilingual Open-Domain Chatbots and Dialogue Evaluators
MARS-Bench: A Multi-turn Athletic Real-world Scenario Benchmark for Dialogue Evaluation
LeCoDe: A Benchmark Dataset for Interactive Legal Consultation Dialogue Evaluation
Methods for Recognizing Nested Terms
RuOpinionNE-2024: Extraction of Opinion Tuples from Russian News Texts
Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models
BoK: Introducing Bag-of-Keywords Loss for Interpretable Dialogue Response Generation
Measuring the Robustness of Reference-Free Dialogue Evaluation Systems
Dialogue You Can Trust: Human and AI Perspectives on Generated Conversations
An Empirical Study on Context Length for Open-Domain Dialog Generation
Soda-Eval: Open-Domain Dialogue Evaluation in the age of LLMs
ECoh: Turn-level Coherence Evaluation for Multilingual Dialogues
On the Benchmarking of LLMs for Open-Domain Dialogue Evaluation
Leveraging LLMs for Dialogue Quality Measurement
LLM as a Scorer: The Impact of Output Order on Dialogue Evaluation
SLIDE: A Framework Integrating Small and Large Language Models for Open-Domain Dialogues Evaluation
PairEval: Open-domain Dialogue Evaluation with Pairwise Comparison
Emphasising Structured Information: Integrating Abstract Meaning Representation into LLMs for Enhanced Open-Domain Dialogue Evaluation
CodingTeachLLM: Empowering LLM's Coding Ability via AST Prior Knowledge
A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators
DialogBench: Evaluating LLMs as Human-like Dialogue Systems
Social Commonsense-Guided Search Query Generation for Open-Domain Knowledge-Powered Conversations
xDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark
RADE: Reference-Assisted Dialogue Evaluation for Open-Domain Dialogue
Exploring the Impact of Human Evaluator Group on Chat-Oriented Dialogue Evaluation
Towards Multilingual Automatic Dialogue Evaluation
Simple LLM Prompting is State-of-the-Art for Robust and Multilingual Dialogue Evaluation
C-PMI: Conditional Pointwise Mutual Information for Turn-level Dialogue Evaluation
Dior-CVAE: Pre-trained Language Models and Diffusion Priors for Variational Dialog Generation
How to Choose How to Choose Your Chatbot: A Massively Multi-System MultiReference Data Set for Dialog Metric Evaluation
DEnsity: Open-domain Dialogue Evaluation Metric using Density Estimation
U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendation
Pragmatically Appropriate Diversity for Dialogue Evaluation
GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
Improving Open-Domain Dialogue Evaluation with a Causal Inference Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.