1openalex_id,contribution_type,description,judged_from,bib_key24387321091,engineering,vLLM / PagedAttention: KV-cache paging for LLM serving; authors report 2-4x throughput at equal latency,abstract,kwon2023vllm34407217670,engineering,vAttention: contiguous virtual memory for the KV cache without PagedAttention; argues paging adds programming and performance overheads,abstract,prabhu2025vattention44404401018,engineering,PowerInfer: GPU-CPU hybrid LLM inference on a consumer GPU exploiting power-law neuron activation locality,abstract,song2024powerinfer54401211704,engineering,Splitwise: prompt and token-generation phases of LLM inference split across machine pools,abstract,patel2024splitwise64394944658,engineering,"Orion: operator-granularity, interference-aware GPU sharing between ML clients",abstract,strati2024orion74394998532,engineering,PyTorch 2 (TorchDynamo/TorchInductor): bytecode-level graph capture and compilation; reported 2.27x inference / 1.41x training geometric-mean speedups,abstract,ansel2024pytorch284393145114,theory,"AI and Memory Wall: argues memory bandwidth, not FLOPS, is the binding constraint for decoder inference (perspective article)",abstract,gholami2024memorywall94406650295,method,AWQ + TinyChat: activation-aware weight quantization and on-device inference framework,abstract,lin2025awq104409568286,survey,"Survey of deep-learning hardware accelerators for heterogeneous HPC platforms (GPU, TPU, FPGA, ASIC, PIM, neuromorphic)",abstract,silvano2025accelerators113111721177,survey,Primer on processing in memory (book chapter),metadata,mutlu2023pim122972087877,survey,Demystifying parallel and distributed deep learning: concurrency analysis of DNN training,abstract,bennun2020demystifying134403931219,engineering,RFC 9669: BPF instruction set architecture standardised by the IETF,metadata,ietf2024rfc9669142783525259,engineering,"Loihi neuromorphic manycore processor with on-chip learning (14 nm, programmable synaptic rules)",abstract,davies2018loihi154210357113,survey,Opportunities for neuromorphic computing algorithms and applications (perspective),metadata,schuman2022neuromorphic164394727812,engineering,Taichi photonic chiplet: diffractive-interference hybrid design; authors report 160 TOPS/W and 1000-category on-chip classification,abstract,xu2024taichi174402694963,survey,Optical neural networks: progress and challenges,abstract,fu2024onn184409283612,engineering,Universal photonic AI acceleration (Nature 2025); abstract unavailable in the corpus,metadata,ahmed2025photonic197128293306,engineering,Neuromorphic photonic circuit with on-chip capacitive analog memory; authors report >26x power saving vs SRAM-DAC in analysis,abstract,lam2026neuromorphicphotonic204321610982,empirical,Surface-code logical qubit scaling d=3 to d=5 on superconducting qubits (Google Quantum AI),abstract,googlequantum2023suppressing214389373471,empirical,"Logical quantum processor on reconfigurable neutral-atom arrays, up to 280 physical qubits",abstract,bluvstein2024logical224380627387,empirical,"127-qubit experiment with accurate expectation values beyond brute-force classical simulation (IBM, 'utility before fault tolerance')",abstract,kim2023utility234405183524,empirical,"Below-threshold surface-code memories (Willow): distance-7 code, logical error suppression factor 2.14 per distance step",abstract,googlequantum2025belowthreshold244408847956,survey,Review of barren plateaus in variational quantum computing,metadata,larocca2025barren254407158326,empirical,Distributed quantum computing across an optical link between two trapped-ion modules (gate teleportation),abstract,main2025distributedqc264406693713,engineering,Aurora: 35-chip modular photonic quantum computer scale model with fibre networking (sub-performant by the authors' description),abstract,aghaee2025aurora274396986598,engineering,Qiskit SDK design and architecture (preprint),abstract,javadiabhari2024qiskit284409126690,survey,"IBM quantum computers: evolution, performance, industry applications",abstract,abughanem2025ibmquantum294321649614,method,Quantum-selected configuration interaction: hybrid quantum-classical ground-state algorithm robust to sampling noise,abstract,kanno2026qsci302781738013,theory,NISQ era framing (Preskill 2018),abstract,preskill2018nisq312982169647,empirical,Quantum supremacy on a 53-qubit programmable superconducting processor,abstract,arute2019supremacy324213212652,survey,Review of noisy intermediate-scale quantum algorithms,abstract,bharti2022nisq334415124086,engineering,"The Faiss library: vector similarity search toolkit, design principles and benchmarks",abstract,douze2026faiss342593864460,engineering,Billion-scale similarity search on GPUs (k-selection design; Faiss),abstract,johnson2021faiss354406085118,survey,"Data-centric AI survey: training-data development, inference-data development, data maintenance",abstract,zha2025datacentric364408444355,empirical,Effects of six data-quality dimensions on 19 ML algorithms (tabular data) under polluted training/test data,abstract,mohammed2025dataquality372963507231,benchmark,BLOCKBENCH: data-processing view of private blockchains and benchmarking framework,abstract,dinh2018blockbench382795038878,method,Datasheets for datasets (documentation standard),abstract,gebru2021datasheets394401857375,survey,Survey of retrieval-augmented LLMs (KDD 2024),abstract,fan2024ragsurvey404394947112,survey,Survey of retrieval-augmented text generation organised as pre-retrieval / retrieval / post-retrieval / generation,abstract,huang2026ragsurvey417118085507,survey,Survey of RAG for AI-generated content across modalities,abstract,zhao2026ragaigc424401834466,survey,Survey of LLMs for recommendation; abstract unavailable in the corpus,metadata,wu2024llmrec434394994587,survey,Recommender systems in the era of LLMs,abstract,zhao2024recsysllm444400531953,benchmark,"C-Pack: C-MTP training data, C-MTEB benchmark and BGE embedding models for Chinese and English",abstract,xiao2024cpack453045200674,method,LightGCN: simplified graph convolution for collaborative filtering (ablation of feature transformation and non-linearity),abstract,he2020lightgcn463097300053,survey,Graph neural networks in recommender systems: survey,abstract,wu2023gnnrec474315977496,survey,"Survey of GNNs for recommender systems: challenges, methods, directions",abstract,gao2023gnnrecsurvey484394946189,engineering,RCACopilot: LLM-based root-cause analysis for cloud incidents; authors report RCA accuracy up to 0.766 on a year of Microsoft incidents,abstract,chen2024rcacopilot494395047770,survey,Review of deep-reinforcement-learning methods for cloud resource scheduling,abstract,zhou2024drlcloud507160863705,engineering,CAPS: carbon-aware prompt scheduling for multi-tenant LLM inference (trace-driven simulation; 26.8% lower carbon per 1K tokens vs round-robin as reported),abstract,liao2026caps517161556515,engineering,DeepServeCB: contextual-bandit elastic scheduling for serverless multi-tenant LLM inference,abstract,li2026deepservecb522930508541,theory,Berkeley view on serverless computing (preprint; position paper),abstract,jonas2019serverless533152809665,engineering,Nightcore: sub-millisecond serverless runtime for interactive microservices,abstract,jia2021nightcore543021475380,engineering,Keystone: open framework for customisable trusted execution environments on RISC-V,abstract,lee2020keystone552950865323,survey,Edge intelligence: survey of AI at the network edge (Proc. IEEE 2019),abstract,zhou2019edgeintelligence564406207083,survey,Mobile edge intelligence for LLMs: contemporary survey,abstract,qu2025meillm577123361055,survey,Edge general intelligence with agentic AI: concepts and technologies,abstract,zhang2026edgegeneral584415028496,survey,Edge-cloud collaborative computing on distributed intelligence and model optimisation: survey,abstract,liu2026eccc597125650829,theory,AI Flow: device-edge-cloud framework for large models (perspective),abstract,an2026aiflow604322576964,survey,"On the road to 6G: visions, requirements, key technologies, testbeds",abstract,wang2023road6g613194620979,survey,Integrated sensing and communications for 6G (JSAC overview),abstract,liu2022isac627127083419,survey,From large AI models to agentic AI: tutorial for intelligent communications,abstract,jiang2026lamagentic637125196921,survey,"Massive IoT: energy, scalability, data and security review",abstract,cheikh2026massiveiot642962883549,survey,Deep learning in mobile and wireless networking: survey,abstract,zhang2019dlwireless653156891177,empirical,"Carbon emissions and large neural network training: energy and CO2e estimates for T5, Meena, GShard, Switch Transformer, GPT-3 (preprint)",abstract,patterson2021carbon664308245305,empirical,"Carbon footprint of BLOOM across its life cycle: 24.7 t CO2e (dynamic) to 50.5 t (full), as reported (preprint)",abstract,luccioni2023bloom674283157527,empirical,Software carbon intensity of AI in cloud instances; argues providers should expose carbon information,abstract,dodge2022carbonintensity684362707075,empirical,Water footprint of AI models (preprint); CACM version li2025thirsty,abstract,li2023thirsty694385481791,empirical,Carbon impact of generative-AI inference today and in 2035; workload model with request-direction policies,abstract,chien2023carbongenai704399913870,survey,"Review of green AI (green-by, green-in, measurement tools, regulation)",abstract,boloncanedo2024greenai714411541921,theory,Jevons' paradox / rebound effects in AI's environmental debate (argumentative paper),abstract,luccioni2025jevons727115707641,theory,Carbon and water footprints of data centres: disclosure gaps and policy (perspective),abstract,devriesgao2026datacenters734415057924,survey,Electricity demand and grid impacts of AI data centres: review and vision,abstract,chen2026aielectricity747138433923,benchmark,TokenPowerBench: benchmark for power consumption of LLM inference with prefill/decode attribution,abstract,niu2026tokenpowerbench754407592994,survey,Green federated learning survey,abstract,thakur2025greenfl76