3 papers
cs.AI2026
HyperLens: Quantifying Cognitive Effort in LLMs with Fine-grained Confidence Trajectory
Chengda Lu, Xiaoyu Fan, Wei Xu
While Large Language Models (LLMs) achieve strong performance across diverse tasks, their inference dynamics remain poorly understood because of the limited resolution of existing…
cs.LG2025
ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning
Yang Wu, Huayi Zhang, Yizheng Jiao +6
Instruction tuning has underscored the significant potential of large language models (LLMs) in producing more human controllable and effective outputs in various domains. In this…
cs.DC2024
KVDirect: Distributed Disaggregated LLM Inference
Shiyang Chen, Rain Jiang, Dezhi Yu +6
Large Language Models (LLMs) have become the new foundation for many applications, reshaping human society like a storm. Disaggregated inference, which separates prefill and decode…