4 papers
Towards Communication-Efficient Decentralized Federated Graph Learning over Non-IID Data
Shilong Wang, Jianchun Liu, Hongli Xu +3
Decentralized Federated Graph Learning (DFGL) overcomes potential bottlenecks of the parameter server in FGL by establishing a peer-to-peer (P2P) communication network among worker…
Adaptive KV-Cache Compression without Manually Setting Budget
Chenxia Tang, Jianchun Liu, Hongli Xu +1
Large language models (LLMs) inference relies heavily on KV-caches to accelerate autoregressive decoding, but the resulting memory footprint grows rapidly with sequence length, pos…
Top-: Not All Logits Are You Need
Chenxia Tang, Jianchun Liu, Hongli Xu +1
Large language models (LLMs) typically employ greedy decoding or low-temperature sampling for reasoning tasks, reflecting a perceived trade-off between diversity and accuracy. We c…
Heterogeneous Learning Rate Scheduling for Neural Architecture Search on Long-Tailed Datasets
Chenxia Tang
In this paper, we attempt to address the challenge of applying Neural Architecture Search (NAS) algorithms, specifically the Differentiable Architecture Search (DARTS), to long-tai…