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Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Action
Methodologically, we propose a resource-efficiency Hopfield retriever to enhance the efficiency and accuracy of conversational information retrieval within our actions.
HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model
We propose a heterogeneous graph mamba network (HGMN) as the first exploration in leveraging the selective state space models (SSSMs) for heterogeneous graph learning.
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
We present a Chain-of-Action (CoA) framework for multimodal and retrieval-augmented Question-Answering (QA).
CoRMF: Criticality-Ordered Recurrent Mean Field Ising Solver
We propose an RNN-based efficient Ising model solver, the Criticality-ordered Recurrent Mean Field (CoRMF), for forward Ising problems.
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