CORTEXA
← Browse

Meng Li

7 papers indexed

arxivcs.AR2026-07-24

HEMERA: A Heterogeneous Memory-Centric Accelerator with Recursive Dataflow for Edge-Constrained State-Space-Duality Models Inference

Hao Ding, Ling Liang, Ruitong Qiao, Dongxue Zhao, Xiantong Qiu, Jinshan Li, et al.

Structured State Space Models (SSMs), such as Mamba, enable efficient long-sequence modeling with linear time complexity. Recent implementations realize this capability through Structured State Space Duality (SSD), which transforms recursive state evolution into matrix-form compu…

View free PDFSource page
arxivcs.DCcs.AIcs.NI2026-07-17

Scalable LLM Agent Tool Access in the Cloud

Mingxin Li, Enge Song, Yueshang Zuo, Xiaodong Liu, Rong Wen, Qiang Fu, et al.

LLM agents increasingly rely on tool calling to act on external systems, and the Model Context Protocol (MCP) has quickly become its de facto interface. Operating MCP at cloud scale, however, becomes difficult. On the tool provider side, legacy services are not directly callable…

View free PDFSource page
arxivcs.AI2026-07-16

SmartRAG: Native Graph-Based RAG for Mobile Device

Zhihan Jiang, Meng Li, Shenghao Liu, Keran Li, Ruiben Zhou, Wei Wang, et al.

Deploying large language models (LLMs) as personal assistants on mobile devices demands privacy, low latency, and offline availability, yet the computational cost of giant models clashes with strict edge-hardware budgets. We argue that this tension cannot be resolved by model com…

View free PDFSource page
arxivcs.ROcs.AI2026-07-14

Jetson-PI: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference

Zebin Yang, Qi Wang, Yunhe Wang, Xiurui Guo, Bo Yu, Shaoshan Liu, et al.

Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard devices, such as the Jetson Orin, remains challenging due to their high computational complexity, which leads to substantial infe…

View free PDFSource page
arxivcs.AIcs.CL2026-07-02

Spec-AUF: Accept-Until-Fail Training under Train-Inference Misalignment for Masked Block Drafters

Tianjian Yang, Meng Li

Speculative decoding accelerates autoregressive generation by drafting a block of tokens that the target model verifies left-to-right, committing only the longest accepted prefix. Block (DLM-style) drafters predict the whole block in parallel, which is fast but trained with a ful…

View free PDFSource page
arxivcs.AI2026-06-30

FARS: A Fully Automated Research System Deployed at Scale

Qiong Tang, Tianxiang Sun, Xiangkun Hu, Xiangyang Liu, Yiran Chen, Yunfan Shao, et al.

Recent automated research systems show that language-model agents can generate hypotheses, run experiments, and write complete manuscripts, but most evidence still comes from selected examples, human-framed topics, or a few pre-defined research tasks. We present FARS (Fully Autom…

View free PDFSource page
crossrefBiomedicines2025-02-25Cited by 3

Insights into the Correlation and Immune Crosstalk Between COVID-19 and Sjögren’s Syndrome Keratoconjunctivitis Sicca via Weighted Gene Coexpression Network Analysis and Machine Learning

Yaqi Cheng, Liang Zhao, Huan Yu, Jiayi Lin, Meng Li, Huini Zhang, et al.

Background: Although autoimmune complications of COVID-19 have aroused concerns, there is no consensus on its ocular complications. Sjögren’s syndrome is an autoimmune disease accompanied by the ocular abnormality keratoconjunctivitis sicca (SS-KCS), which may be influenced by CO…

View free PDFSource page