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Gangqiang Hu

2 accepted papers

2026

LLMs are Single-threaded Reasoners: Demystifying the Working Mechanism of Soft Thinking

ICLR 2026poster

Human cognition naturally engages with abstract and fluid concepts, whereas existing reasoning models often rely on generating discrete tokens, potentially constraining their expressive capabilities. Recent advancements aim to address this limitation by enabling large language models (LLMs) to gener…

Cited by 0SourceScholar
2025

TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning

AAAI 2025technical

Due to the sensitivity of data, Federated Learning (FL) is employed to enable distributed machine learning while safeguarding data privacy and accommodating the requirements of various devices. However, in the context of semidecentralized FL, clients’ communication and training states are dynamic. T…

Cited by 0SourcePDFScholar