11 citations · 32 across the 6 of their papers we have counts for
6 papers
A Survey on the Memory Mechanism of Large Language Model based Agents
Zeyu Zhang, Xiaohe Bo, Chen Ma +6
Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are feature…
Only Encode Once: Making Content-based News Recommender Greener
Qijiong Liu, Jieming Zhu, Quanyu Dai +1
Large pretrained language models (PLM) have become de facto news encoders in modern news recommender systems, due to their strong ability in comprehending textual content. These hu…
Out-of-distribution Detection with Implicit Outlier Transformation
Qizhou Wang, Junjie Ye, Feng Liu +5
Outlier exposure (OE) is powerful in out-of-distribution (OOD) detection, enhancing detection capability via model fine-tuning with surrogate OOD data. However, surrogate data typi…
REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation
Xu Chen, Jingsen Zhang, Lei Wang +6
Explainable recommendation has attracted much attention from the industry and academic communities. It has shown great potential for improving the recommendation persuasiveness, in…
Debiased Recommendation with Neural Stratification
Quanyu Dai, Zhenhua Dong, Xu Chen
Debiased recommender models have recently attracted increasing attention from the academic and industry communities. Existing models are mostly based on the technique of inverse pr…
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges
Peng Wu, Haoxuan Li, Yuhao Deng +6
Recently, recommender system (RS) based on causal inference has gained much attention in the industrial community, as well as the states of the art performance in many prediction a…