10 citations · 17 across the 10 of their papers we have counts for
11 papers
To Keep or Not to Keep: Learning KV Cache Retention in Disaggregated LLM Serving Systems
Dong Liu, Yanxuan Yu, Eric Jiang +2
Disaggregated \textsc{LLM} serving separates prefill and decode across node pools, placing a network fabric between \textsc{KV}-cache computation and consumption. This breaks a key…
RUBRIC: Realism--Utility Balanced Ranking for Imbalanced Classification
Yanxuan Yu, Dong Liu, Shu Wang +9
Class imbalance poses a fundamental challenge in risk-sensitive applications such as fraud detection and medical diagnosis, where minority-class samples are scarce yet critical for…
HSMLA: Hierarchical Softmax Multi-scale Linear Attention for Efficient Vision Transformers
Dong Liu, Yanxuan Yu, Renata Borovica-Gajic +2
Vision transformers face significant computational overheads in high-resolution dense prediction due to the quadratic complexity of self-attention. Linear attention offers efficien…
A-SR: Self-Evolving Agentic LLMs for Symbolic Regression via Hierarchical Coordination
Wenxiao Zhao, Dong Liu, Kaiyi Xu +9
Symbolic regression aims to discover closed-form equations from data, but existing LLM-guided methods often rely on a unified proposal loop that compresses heterogeneous search fai…
Thoughts-as-Planning: Latent World Models for Chain-of-Thoughts Optimization via Reinforcement Planning
Dong Liu, Yanxuan Yu, Ying Nian Wu
The success of large language models (LLMs) across diverse NLP tasks has elevated the importance of reasoning chain optimization as a critical step in aligning model behavior with…
MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning
Dong Liu, Yanxuan Yu, Ben Lengerich +1
As long-context language modeling becomes increasingly important, the cost of maintaining and attending to large Key/Value (KV) caches grows rapidly, becoming a major bottleneck in…
Visual Fourier Prompt Tuning
Runjia Zeng, Cheng Han, Qifan Wang +5
With the scale of vision Transformer-based models continuing to grow, finetuning these large-scale pretrained models for new tasks has become increasingly parameter-intensive. Visu…
Visual Agents as Fast and Slow Thinkers
Guangyan Sun, Mingyu Jin, Zhenting Wang +7
Achieving human-level intelligence requires refining cognitive distinctions between System 1 and System 2 thinking. While contemporary AI, driven by large language models, demonstr…
Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models
Chuan Liu, Chunshu Wu, Shihui Cao +8
The rapid development of AI highlights the pressing need for sustainable energy, a critical global challenge for decades. Nuclear fusion, generally seen as an ultimate solution, ha…
Inertial Confinement Fusion Forecasting via Large Language Models
Mingkai Chen, Taowen Wang, Shihui Cao +10
Controlled fusion energy is deemed pivotal for the advancement of human civilization. In this study, we introduce , a novel integration of Large Language Models (…
Image Translation as Diffusion Visual Programmers
Cheng Han, James C. Liang, Qifan Wang +5
We introduce the novel Diffusion Visual Programmer (DVP), a neuro-symbolic image translation framework. Our proposed DVP seamlessly embeds a condition-flexible diffusion model with…