most citedKVDirect: Distributed Disaggregated LLM Inference

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

Human Demonstrations as Post-Training Data for Any Robot Body: Retargeting the Object, Not the Hand

Nagasrikanth Kallakuri

Human demonstrations are today used largely for pretraining vision-language-action models, with little ability to use the same data for target-embodiment or task-oriented training,…

cs.AI2026

HeadWiseKV: Budgeted Per-Head Cache Residency for Hybrid Long-Context Language Models

Renjie Xie, Juncheng Yang, Aoting Hu +4

Long-context inference retains a growing key--value (KV) cache during decoding, which consumes substantial GPU memory and can reduce generation throughput. This bottleneck remains…

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.DC2024★ 1 cited

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…

cs.LG2024

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…