3 citations · 5 across the 5 of their papers we have counts for
6 papers
LazyEviction: Lagged KV Eviction with Attention Pattern Observation for Efficient Long Reasoning
Haoyue Zhang, Hualei Zhang, Xiaosong Ma +2
Large Language Models (LLMs) exhibit enhanced capabilities by Chain-of-Thought reasoning. However, the extended reasoning sequences introduce significant GPU memory overhead due to…
United Minds or Isolated Agents? Exploring Coordination of LLMs under Cognitive Load Theory
HaoYang Shang, Xuan Liu, Zi Liang +3
Large Language Models (LLMs) exhibit a notable performance ceiling on complex, multi-faceted tasks. As practitioners increasingly rely on heavy context engineering -- curating intr…
Exploring Prosocial Irrationality for LLM Agents: A Social Cognition View
Xuan Liu, Jie Zhang, Haoyang Shang +3
Large language models (LLMs) have been shown to face hallucination issues due to the data they trained on often containing human bias; whether this is reflected in the decision-mak…
SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization
Yingchun Wang, Jingcai Guo, Yi Liu +4
Model substructure learning aims to find an invariant network substructure that can have better out-of-distribution (OOD) generalization than the original full structure. Existing…
Data Quality-aware Mixed-precision Quantization via Hybrid Reinforcement Learning
Yingchun Wang, Jingcai Guo, Song Guo +1
Mixed-precision quantization mostly predetermines the model bit-width settings before actual training due to the non-differential bit-width sampling process, obtaining sub-optimal…
Towards Fairer and More Efficient Federated Learning via Multidimensional Personalized Edge Models
Yingchun Wang, Jingcai Guo, Jie Zhang +3
Federated learning (FL) is an emerging technique that trains massive and geographically distributed edge data while maintaining privacy. However, FL has inherent challenges in term…