most citedTowards Explainable Conversational Recommender Systems

35 citations · 52 across the 4 of their papers we have counts for

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cs.IR2025

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models

Zhengliang Shi, Lingyong Yan, Weiwei Sun +7

Retrieval-augmented generation (RAG) integrates large language models ( LLM s) with retrievers to access external knowledge, improving the factuality of LLM generation in knowledge…

cs.IR2025

Replication and Exploration of Generative Retrieval over Dynamic Corpora

Zhen Zhang, Xinyu Ma, Weiwei Sun +6

Generative retrieval (GR) has emerged as a promising paradigm in information retrieval (IR). However, most existing GR models are developed and evaluated using a static document co…

cs.IR202335 cited

Towards Explainable Conversational Recommender Systems

Shuyu Guo, Shuo Zhang, Weiwei Sun +3

Explanations in conventional recommender systems have demonstrated benefits in helping the user understand the rationality of the recommendations and improving the system's efficie…

cs.IR202316 cited

Learning to Tokenize for Generative Retrieval

Weiwei Sun, Lingyong Yan, Zheng Chen +7

Conventional document retrieval techniques are mainly based on the index-retrieve paradigm. It is challenging to optimize pipelines based on this paradigm in an end-to-end manner.…

cs.IR20221 cited

Adaptive Structural Similarity Preserving for Unsupervised Cross Modal Hashing

Liang Li, Baihua Zheng, Weiwei Sun

Cross-modal hashing is an important approach for multimodal data management and application. Existing unsupervised cross-modal hashing algorithms mainly rely on data features in pr…