1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Enabling Federated Inference via Unsupervised Consensus Embedding
Yui Hashimoto, Takayuki Nishio, Yuichi Kitagawa +1
Cooperative inference across independently deployed machine learning models is increasingly desirable in distributed environments, as there is a growing need to leverage multiple m…
cs.CL2026
Spatiotemporal Hidden-State Dynamics as a Signature of Internal Reasoning in Large Language Models
Kotaro Furuya, Takahito Tanimura
Large reasoning models (LRMs) generate extended solutions, yet it remains unclear whether these traces reflect substantive internal computation or merely verbosity and overthinking…
cs.LG2026★ 1 cited
Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation
Kitsuya Azuma, Takayuki Nishio, Yuichi Kitagawa +2
Federated Learning (FL) enables collaborative model training across decentralized clients, enhancing privacy by keeping data local. Yet conventional FL, relying on frequent paramet…