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DiQAD: A Benchmark Dataset for Open-domain Dialogue Quality Assessment., , , , , , , and . EMNLP (Findings), page 15128-15145. Association for Computational Linguistics, (2023)Pre-trained Language Model-based Retrieval and Ranking for Web Search., , , , , , , , , and 2 other author(s). ACM Trans. Web, 17 (1): 4:1-4:36 (February 2023)A Simple yet Effective Framework for Active Learning to Rank., , , , , , , , , and . Mach. Intell. Res., 21 (1): 169-183 (February 2024)Practical Strategies of Active Learning to Rank for Web Search., , , , , , , , , and 1 other author(s). CoRR, (2022)First Target and Opinion then Polarity: Enhancing Target-opinion Correlation for Aspect Sentiment Triplet Extraction., , , , , , , and . CoRR, (2021)PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation., , , , , , , , and . EMNLP (Industry Track), page 587-595. Association for Computational Linguistics, (2022)MA4DIV: Multi-Agent Reinforcement Learning for Search Result Diversification., , , , , , , , , and . CoRR, (2024)Actively predicting diverse search intent from user browsing behaviors., , and . WWW, page 221-230. ACM, (2010)DiQAD: A Benchmark Dataset for End-to-End Open-domain Dialogue Assessment., , , , , , , and . CoRR, (2023)Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction., , , , , , , , and . CoRR, (2023)