4 citations · 5 across the 5 of their papers we have counts for
5 papers
RaSeRec: Retrieval-Augmented Sequential Recommendation
Xinping Zhao, Baotian Hu, Yan Zhong +5
Although prevailing supervised and self-supervised learning augmented sequential recommendation (SeRec) models have achieved improved performance with powerful neural network archi…
DUAL-REFLECT: Enhancing Large Language Models for Reflective Translation through Dual Learning Feedback Mechanisms
Andong Chen, Lianzhang Lou, Kehai Chen +5
Recently, large language models (LLMs) enhanced by self-reflection have achieved promising performance on machine translation. The key idea is guiding LLMs to generate translation…
Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?
Zhaochen Su, Juntao Li, Jun Zhang +6
Temporal reasoning is fundamental for large language models (LLMs) to comprehend the world. Current temporal reasoning datasets are limited to questions about single or isolated ev…
TasTe: Teaching Large Language Models to Translate through Self-Reflection
Yutong Wang, Jiali Zeng, Xuebo Liu +3
Large language models (LLMs) have exhibited remarkable performance in various natural language processing tasks. Techniques like instruction tuning have effectively enhanced the pr…
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community
Qingyao Ai, Ting Bai, Zhao Cao +30
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Mod…