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Dialogue Evaluation

Papers

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Showing 26–50 of 97 papers

TitleStatusHype
Achieving Reliable Human Assessment of Open-Domain Dialogue Systems—0
Improving Open-Domain Dialogue Evaluation with a Causal Inference Model—0
Investigating the Impact of Pre-trained Language Models on Dialog Evaluation—0
Joint Goal Segmentation and Goal Success Prediction on Multi-Domain Conversations—0
Learning the Human Judgment for the Automatic Evaluation of Chatbot—0
LeCoDe: A Benchmark Dataset for Interactive Legal Consultation Dialogue Evaluation—0
Leveraging LLMs for Dialogue Quality Measurement—0
LLM as a Scorer: The Impact of Output Order on Dialogue Evaluation—0
MARS-Bench: A Multi-turn Athletic Real-world Scenario Benchmark for Dialogue Evaluation—0
DCH-2: A Parallel Customer-Helpdesk Dialogue Corpus with Distributions of Annotators' Labels—0
AdaCoach: A Virtual Coach for Training Customer Service Agents—0
ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisons—0
MME-CRS: Multi-Metric Evaluation Based on Correlation Re-Scaling for Evaluating Open-Domain Dialogue—0
One "Ruler" for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning—0
On the Benchmarking of LLMs for Open-Domain Dialogue Evaluation—0
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment—0
Pragmatically Appropriate Diversity for Dialogue Evaluation—0
Predicting Ratings of Real Dialogue Participants from Artificial Data and Ratings of Human Dialogue Observers—0
Dialogue Evaluation with Offline Reinforcement Learning—0
RADE: Reference-Assisted Dialogue Evaluation for Open-Domain Dialogue—0
Re-evaluating ADEM: A Deeper Look at Scoring Dialogue Responses—0
Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges—0
Dialogue You Can Trust: Human and AI Perspectives on Generated Conversations—0
DRE: An Effective Dual-Refined Method for Integrating Small and Large Language Models in Open-Domain Dialogue Evaluation—0
Enhancing the Open-Domain Dialogue Evaluation in Latent Space—0
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All datasetsUSR-TopicalChatUSR-PersonaChat

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MDD-EvalSpearman Correlation0.51—Unverified
2Lin-Reg (all)Spearman Correlation0.49—Unverified
3USRSpearman Correlation0.42—Unverified
4USR - DR (x = c)Spearman Correlation0.32—Unverified
5USR - MLMSpearman Correlation0.31—Unverified
6USR - DR (x = f)Spearman Correlation0.14—Unverified
#ModelMetricClaimedVerifiedStatus
1Lin-Reg (all)Spearman Correlation0.54—Unverified
2USR - DR (x = c)Spearman Correlation0.48—Unverified
3USRSpearman Correlation0.47—Unverified
4USR - MLMSpearman Correlation0.08—Unverified
5USR - DR (x = f)Spearman Correlation-0.05—Unverified