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20242026
most citedHierarchical Micro-Segmentations for Zero-Trust Services via Large Language Model (LLM)-enhanced Graph Diffusion

2 citations · 3 across the 25 of their papers we have counts for

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9 papers · 1 filter

cs.NI2026

NebulaSD: Many-for-Many Speculative Decoding

Junhao He, Hongyang Du

Speculative decoding accelerates Large Language Model (LLM) inference by using a lightweight draft model to propose candidate tokens for parallel verification by a target model. Dr…

cs.AI2026

Designer-RSI: Evolving Procedural Memory from User Traffic for Agentic Graphic Design

Hongyang Du, Lan Yan, Christian Flores +1

Professional graphic design is a long-horizon agentic task in which structured, editable artifacts emerge from many interdependent actions, yet outcomes admit no reliable programma…

cs.CL2026

CROP: Task Relevance via Counterfactuals for Selective On-Policy Distillation

Enhan Li, Junhao He, Hongyang Du

On-policy distillation (OPD) supervises a student language model on trajectories sampled from its current policy, but assigns equal credit to response tokens with unequal supervisi…

cs.NI2026

HACO: Hedged Agent Computing for Reliable LLM Systems

Enhan Li, Hongyang Du

As large language model (LLM) agents move from isolated prompting to longhorizon workflows, failures increasingly arise at the role-to-instance binding boundary, where task-specifi…

cs.NI2026

MORES: Mobile Reasoning-as-a-Service via Distributed LLM Inference-Time Scaling

Guanchen Liu, Hongyang Du, Kaibin Huang

Inference-time scaling has emerged as an effective approach for enhancing the capabilities of Large Language Models (LLMs), addressing the growing demand for stronger reasoning wit…

cs.DC2026

Multi-SPIN: Multi-Access Speculative Inference for Cooperative Token Generation at the Edge

Haotian Zheng, Zhanwei Wang, Mingyao Cui +3

Speculative inference (SPIN) was originally developed as an efficient architecture to accelerate Large Language Models (LLMs). In this work, we propose its distributed deployment t…