collaborators

9 papers

cs.CL2026

CentroidKV: Efficient Long-Context LLM Inference via KV Cache Clustering

Jie Hu, Shengnan Wang, Yutong He +8

Large language models (LLMs) with extended context windows have become increasingly prevalent for tackling complex tasks. However, the substantial Key-Value (KV) cache required for…

cs.SE2026

Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought

Lingzhe Zhang, Tong Jia, Kangjin Wang +8

As modern microservice systems grow increasingly complex due to dynamic interactions and evolving runtime environments, they experience failures with rising frequency. Ensuring sys…

cs.CL2026

AtlasKV: Augmenting LLMs with Billion-Scale Knowledge Graphs in 20GB VRAM

Haoyu Huang, Hong Ting Tsang, Jiaxin Bai +3

Retrieval-augmented generation (RAG) has shown some success in augmenting large language models (LLMs) with external knowledge. However, as a non-parametric knowledge integration p…

cs.AI2026

M2F: Automated Formalization of Mathematical Literature at Scale

Zichen Wang, Wanli Ma, Zhenyu Ming +3

Automated formalization of mathematics enables mechanical verification but remains limited to isolated theorems and short snippets. Scaling to textbooks and research papers is larg…

cs.CL2026

HyLRA: Hybrid Layer Reuse Attention for Efficient Long-Context Inference

Xuan Ai, Qingqing Yang, Peng Wang +4

Long-context inference in Large Language Models (LLMs) is bottlenecked by the quadratic computation complexity of attention and the substantial memory footprint of Key-Value (KV) c…

cs.LG2026

Uni-FinLLM: A Unified Multimodal Large Language Model with Modular Task Heads for Micro-Level Stock Prediction and Macro-Level Systemic Risk Assessment

Gongao Zhang, Haijiang Zeng, Lu Jiang

Financial institutions and regulators require systems that integrate heterogeneous data to assess risks from stock fluctuations to systemic vulnerabilities. Existing approaches oft…