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Network Intelligence Research Center (NIRC)
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Network Intelligence Research Center (NIRC)

NIRC is based on the National Key Laboratory of Network and Switching Technology at Beijing University of Posts and Telecommunications. It has built a technology matrix across four AI domains—intelligent cloud networking, natural language processing, computer vision, and machine learning systems—dedicated to solving real‑world problems, creating top‑tier systems, publishing high‑impact papers, and contributing significantly to the rapid advancement of China's network technology.

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Recent Articles

Latest from Network Intelligence Research Center (NIRC)

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Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 31, 2025 · Artificial Intelligence

Why AI Inference Is Slow and How Cutting‑Edge Tech Boosts It in Industrial Settings

The article analyzes the severe inference bottlenecks of large language models, CNNs, and recommendation systems and presents a suite of research‑driven accelerations—including token‑level pipeline parallelism (HPipe), KV‑cache clustering (ClusterAttn), quantization (QoKV), heterogeneous edge frameworks (DeepZoning, PICO), delay‑aware edge‑cloud scheduling (DECC), and operator choreography (RACE)—validated on real‑world industrial workloads.

AI inferenceHeterogeneous Computingedge AI
0 likes · 16 min read
Why AI Inference Is Slow and How Cutting‑Edge Tech Boosts It in Industrial Settings
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 30, 2025 · Artificial Intelligence

Bridging Tokenizer Gaps: Cross-Tokenizer Knowledge Distillation at AAAI 2026

This paper introduces SeDi, a semantics‑ and distribution‑aware cross‑tokenizer knowledge distillation framework that aligns teacher and student token spaces via bipartite graph components and top‑K re‑encoding, achieving state‑of‑the‑art performance and lower exposure bias on multiple LLM benchmarks.

AI researchSemantic Alignmentcross-tokenizer distillation
0 likes · 10 min read
Bridging Tokenizer Gaps: Cross-Tokenizer Knowledge Distillation at AAAI 2026
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 26, 2025 · Artificial Intelligence

Introducing MCP: A Standard Protocol to Empower Large Models with System Capabilities

MCP (Model Context Protocol) is an open standard that lets AI applications connect to external systems through a unified client‑server model, exposing Tools, Resources, and Prompts, while addressing security, permission, and audit concerns to make large‑model deployments more reusable and controllable.

AI integrationTool Callingmodel context protocol
0 likes · 4 min read
Introducing MCP: A Standard Protocol to Empower Large Models with System Capabilities
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 23, 2025 · Artificial Intelligence

ClusterAttn: Compressing KV Cache with Intrinsic Attention Clustering

ClusterAttn tackles the KV‑cache bottleneck of large language models by exploiting the natural clustering of attention scores, achieving up to 92% compression without accuracy loss, boosting throughput 2.6–4.8×, handling 128K‑token sequences on a single GPU, and outperforming existing training‑free compression methods.

KV cache compressionattention clusteringdensity clustering
0 likes · 8 min read
ClusterAttn: Compressing KV Cache with Intrinsic Attention Clustering
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 19, 2025 · Databases

DIVER: A Robust Text-to-SQL System Unveiled at SIGMOD 2026, Powering ChatBI

The paper introduces DIVER, an automated expert system that gives large language models human‑like exploration, reasoning, and verification abilities for Text‑to‑SQL, addressing the severe performance drop without expert evidence by innovating dynamic interactive value linking, multi‑agent automation, and adaptive evidence generation, and demonstrates up to 10.82% accuracy gains and strong robustness on real‑world benchmarks.

Automated Expert AgentChatBIDIVER
0 likes · 11 min read
DIVER: A Robust Text-to-SQL System Unveiled at SIGMOD 2026, Powering ChatBI
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 15, 2025 · Artificial Intelligence

Turning LLM-Generated Network Configurations into Verified, Safe Updates with Artanis

The paper introduces Artanis, an intent‑based network configuration update framework that combines large‑language‑model generation with a verification‑feedback loop and reinforcement‑learning optimization, addressing hallucination‑induced errors and ensuring safe, policy‑compliant deployments across diverse network scales.

Intent-based NetworkingLLMconfiguration management
0 likes · 9 min read
Turning LLM-Generated Network Configurations into Verified, Safe Updates with Artanis
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Dec 5, 2025 · R&D Management

Linking Zotero and Obsidian: From Paper Collection to Visual Knowledge Graph

This guide walks graduate researchers through a step‑by‑step workflow—collecting papers with Zotero, translating them via an LLM plugin, generating structured markdown notes, and then using Obsidian’s bidirectional links and Canvas to build a local, visual knowledge graph that ties individual citations into a coherent research map.

Knowledge GraphLLM TranslationObsidian
0 likes · 4 min read
Linking Zotero and Obsidian: From Paper Collection to Visual Knowledge Graph
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Nov 24, 2025 · Artificial Intelligence

Simplifying AI Operator Development with TileLang DSL

TileLang is a Python‑style DSL built on TVM that separates algorithm logic from hardware scheduling, offers beginner to expert interfaces, supports multiple GPU and CPU backends, and delivers performance on par with or better than existing AI kernels, as demonstrated with GEMM, FlashAttention and other benchmarks.

AI operatorsGEMMGPU
0 likes · 10 min read
Simplifying AI Operator Development with TileLang DSL