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Found 6 papers, 5 papers with code
JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving
Specially, we construct a Mixture-of-Experts~(MoE) architecture for modeling mathematical text, so as to capture the common mathematical knowledge across tasks.
JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding
Considering the complex nature of mathematical texts, we design a novel curriculum pre-training approach for improving the learning of mathematical PLMs, consisting of both basic and advanced courses.
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System
To implement this framework, we design both coarse-grained and fine-grained procedures for modeling user preference, where the former focuses on more general, coarse-grained semantic fusion and the latter focuses on more specific, fine-grained semantic fusion.
Ranked #1 on
Recommendation Systems
on ReDial
CRSLab: An Open-Source Toolkit for Building Conversational Recommender System
In recent years, conversational recommender system (CRS) has received much attention in the research community.
Towards Topic-Guided Conversational Recommender System
To develop an effective CRS, the support of high-quality datasets is essential.
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
Conversational recommender systems (CRS) aim to recommend high-quality items to users through interactive conversations.
Ranked #3 on
Text Generation
on ReDial
