Thinking Like an Expert:Multimodal Hypergraph-of-Thought (HoT) Reasoning to boost Foundation Modals

no code implementations • 11 Aug 2023 • Fanglong Yao, Changyuan Tian, Jintao Liu, Zequn Zhang, Qing Liu, Li Jin, Shuchao Li, Xiaoyu Li, Xian Sun

Inspired by this, this paper innovatively proposes a multimodal Hypergraph-of-Thought (HoT) reasoning paradigm, which enables the foundation models to possess the expert-level ability of high-order multi-hop reasoning and multimodal comparative judgement.

Graph Learning Logical Reasoning

Context-aware Tree-based Deep Model for Recommender Systems

no code implementations • 22 Sep 2021 • Daqing Chang, Jintao Liu, Ziru Xu, Han Li, Han Zhu, Xiaoqiang Zhu

Vertically, a parent fusion layer is designed in M to transmit the user preference representation in higher levels of T to the current level, grasping the essence that tree-based methods are generating the candidate set from coarse to detail during the beam search retrieval.

Recommendation Systems Retrieval

Deep learning for smart fish farming: applications, opportunities and challenges

no code implementations • 6 Apr 2020 • Xinting Yang, Song Zhang, Jintao Liu, Qinfeng Gao, Shuanglin Dong, Chao Zhou

This change can create new opportunities and a series of challenges for information and data processing in smart fish farming.

Decision Making

Transformer-Based Capsule Network For Stock Movement Prediction

no code implementations • WS 2019 • Jintao Liu, Hongfei Lin, Xikai Liu, Bo Xu, Yuqi Ren, Yufeng Diao, Liang Yang