Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:07:38.016961Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2608.06989.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:07:38.016961Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
68 of 68 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM cublas docs,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM High bandwidth memory dram (hbm1, hbm2) jesd235d,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Analyzing cuda workloads using a detailed gpu simulator,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Moe-lightning: High-throughput moe inference on memory-constrained gpus,
Reference 4
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,
Reference 5
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Palm: Scal- ing language modeling with pathways,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Asap7: A 7-nm finfet predictive process design kit,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Deepseekmoe: Towards ultimate expert special- ization in mixture-of-experts language models,
Reference 9
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM The true processing in memory accelerator,
Reference 10
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Observation b71ffb43-2818-4c36-af5b-cf38e62eec34 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Accelerating llm inference throughput via asynchronous kv cache prefetching,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM The Llama 3 Herd of Models
Reference 12
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Observation 2b136343-57ca-44f0-93c7-7c43136ff078 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Klotski: Efficient mixture-of-expert inference via expert- aware multi-batch pipeline,
Reference 13
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,
Reference 14
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Observation d274dc01-2f97-413f-ab86-9d08951e2c2c · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM The future of low-latency memory: Why near memory requires a new interface,
Reference 15
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Papi: Exploiting dynamic parallelism in large language model decoding with a processing-in-memory-enabled computing system,
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Neupims: Npu-pim heterogeneous acceleration for batched llm inferencing,
Reference 17
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Lightllm: A versatile large language model for predictive light sensing,
Reference 18
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Decoding llm performance—prefill phase is compute bound on npu,
Reference 19
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Mixtral of Experts
Reference 20
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Observation ae003cce-039d-4a6a-aa1f-6631b5566e1d · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM The battle of chatbot giants: an ex- perimental comparison of chatgpt and bard,
Reference 21
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Accel-sim: An extensible simulation framework for validated gpu modeling,
Reference 22
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Sk hynix ai-specific computing memory solution: From aim device to heterogeneous aimx-xpu system for comprehensive llm inference,
Reference 23
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Observation afacd144-eb5c-4f26-9bca-40082e3e05fc · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Monde: Mixture of near-data experts for large-scale sparse models,
Reference 24
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Efficient memory management for large language model serving with pagedattention,
Reference 25
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Observation 6b992dcc-1456-4ffe-9245-e8a383c00909 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM vllm: Easy, fast, and cheap llm serving for everyone
Reference 26
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Observation 1b98ec61-3a59-4a96-bfbc-b047e080cf63 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM A 1ynm 1.25 v 8gb, 16gb/s/pin gddr6-based accelerator-in-memory supporting 1tflops mac operation and various activation functions for deep-learning applications,
Reference 27
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Observation 42c4c93d-eb61-4471-be5a-5da3eb13c67a · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Hardware architecture and software stack for pim based on commercial dram technology: Industrial product,
Reference 28
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Observation e8f5c68a-4265-4551-9b81-93b293924ff5 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM H2-llm: Hardware-dataflow co-exploration for heterogeneous hybrid-bonding-based low-batch llm inference,
Reference 29
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Ascend: a scalable and unified architecture for ubiquitous deep neural network computing: Industry track paper,
Reference 30
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Observation d54ef2b4-5686-4447-8c92-cb43a559cf07 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Davinci: A scalable architecture for neural network computing,
Reference 31
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Observation 883731a9-3936-4704-9b81-bae3e3063d8e · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM DeepSeek-V3 Technical Report
Reference 32
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Ramulator 2.0: A modern, modular, and extensible dram simulator,
Reference 33
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM The design process for google’s training chips: Tpuv2 and tpuv3,
Reference 34
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Observation 168726cf-77ee-4eea-8682-0b9035b2d1a5 · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Nvidia a100 tensor core gpu architecc ture,
Reference 35
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Nvidia h100 tensor core gpu architecture,
Reference 37
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Chatgpt,
Reference 38
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Reference 40
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Attacc! unleashing the power of pim for batched transformer- based generative model inference,
Reference 41
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Observation c7f2f9ad-fd01-4eeb-b859-ee9cb25b790f · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Pytorch: An imperative style, high-performance deep learning library,
Reference 42
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Observation adcbebf4-df7a-45c7-aab6-28ec5758aefd · outbound
Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Splitwise: Efficient generative llm inference using phase splitting,
Reference 43
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Observation 05ba398e-7adb-45ab-ba9c-aa9d5b2a9f79 · outbound
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Reference 44
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Ramulator 2.0,
Reference 46
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Reference 47
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Ianus: Integrated accelerator based on npu-pim unified memory system,
Reference 48
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Reference 49
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Observation b49f68be-cefb-4d46-b4dd-8d348a120514 · outbound
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Reference 50
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Reference 51
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Reference 53
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Reference 54
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Reference 56
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Pim gpt a hybrid process in memory accelerator for autoregressive transformers,
Reference 57
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Reference 58
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Reference 59
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Reference 60
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Reference 61
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Reference 62
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Rethinking Unified Memory for NPU-PIM Systems: Dual-View Memory for Dynamic Inference of LLM Lmsys-chat-1m: A large-scale real-world llm conversation dataset,
Reference 63
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Reference 64
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Reference 65
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Reference 66
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Reference 67
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Reference 2020
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No inbound Pith citation observations are available.