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Paper Citation Record · LEDGER

Architectural Implications of Agentic AI Workflows

As of 10 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 0 inbound Pith citation observations for arXiv:2608.04458.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.04458 v1

Coverage vector

measured 86 of 86 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:49:21.427575Z

measured 86 of 86 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

86 of 86 outbound references displayed

  • verified exact2
  • verified fuzzy50
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d8d5178-6b93-4493-87da-f476a6ce2957 · outbound

This paper cites Software-Defined Agentic Serving,.

Architectural Implications of Agentic AI Workflows Software-Defined Agentic Serving,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c0c094a0-54c2-49b1-a376-7e293a6575be · outbound

This paper cites Micro-Sliced Virtual Processors to Hide the Effect of Discontinuous CPU Availability for Consolidated Systems,.

Architectural Implications of Agentic AI Workflows Micro-Sliced Virtual Processors to Hide the Effect of Discontinuous CPU Availability for Consolidated Systems,

Reference 2

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source=pdf_text observed=2026-08-06T23:49:12.391886Z digest=sha256:7a421ad1541e7cdc60a36848a84b90af640ade5e2869e8fb098d669704ae0a3a

Observation 3cb3c67c-0732-4b33-b3fe-af6857632992 · outbound

This paper cites LLM in a flash: Efficient Large Language Model Inference with Limited Memory.

Architectural Implications of Agentic AI Workflows LLM in a flash: Efficient Large Language Model Inference with Limited Memory

Reference 3

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source=pdf_text observed=2026-08-06T23:49:12.501057Z digest=sha256:95da52a6a203e1407faec6ea065aa0fd6cb4b96e03435d81ea311f93fe468509

Observation e799a95d-6bfa-4589-b24f-8a28811bd520 · outbound

This paper cites Agentic AI with AWS Databases,.

Architectural Implications of Agentic AI Workflows Agentic AI with AWS Databases,

Reference 4

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source=pdf_text observed=2026-08-06T23:49:12.644868Z digest=sha256:f1298d7a030b650e85a05a6db36bd7b5a8eafe336429b4a94751d7a6d501c3ac

Observation 2dc3d2e9-a8fa-42ed-a424-143ed48e6d9b · outbound

This paper cites Agent Computers. Powering the Future of Agentic AI.

Architectural Implications of Agentic AI Workflows Agent Computers. Powering the Future of Agentic AI

Reference 5

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source=pdf_text observed=2026-08-06T23:49:12.787123Z digest=sha256:53b7fe18c875bc28cb7217b5f2f59ce0fd060b7d0357e1b503f4012b5f4bf252

Observation 860d99e0-d274-41fe-8970-3db7d7de1ff6 · outbound

This paper cites Processing Architecture for Power Efficiency and Performance,.

Architectural Implications of Agentic AI Workflows Processing Architecture for Power Efficiency and Performance,

Reference 6

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source=pdf_text observed=2026-08-06T23:49:12.948472Z digest=sha256:fdd74121071207d3fe11668efe8668bf255ce67b432b6bb8cbd8ba19c58ae1b8

Observation 961022b7-f037-4938-88bc-a9c026f6452d · outbound

This paper cites Arm AGI CPU: The world’s most efficient agentic CPU,.

Architectural Implications of Agentic AI Workflows Arm AGI CPU: The world’s most efficient agentic CPU,

Reference 7

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source=pdf_text observed=2026-08-06T23:49:13.254016Z digest=sha256:11fcd824b945cebfdc46f29fb4a912589e7cf6000a1139f01b961d3db3789845

Observation dd0f6d93-20a2-47bb-bf55-73ca6391e988 · outbound

This paper cites Efficient and Scalable Agentic AI with Heterogeneous Systems.

Architectural Implications of Agentic AI Workflows Efficient and Scalable Agentic AI with Heterogeneous Systems

Reference 8

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source=pdf_text observed=2026-08-06T23:49:13.400815Z digest=sha256:fbc6934a706733c4276cdb2695b57bb2365df9b3d5acda876946379f58346bab

Observation 6252d1da-b9a1-4228-825c-b1517bd9f5b9 · outbound

This paper cites Small Language Models are the Future of Agentic AI.

Architectural Implications of Agentic AI Workflows Small Language Models are the Future of Agentic AI

Reference 9

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source=pdf_text observed=2026-08-06T23:49:13.524076Z digest=sha256:e03d4b9872b1c53ded379e8b32632e88ea777644b15680e0ea423e8729bbc44e

Observation eabaa710-b3a0-4967-b071-8df750b680fa · outbound

This paper cites TokenDance: Scaling Multi-Agent LLM Serving via Collective KV Cache Sharing.

Architectural Implications of Agentic AI Workflows TokenDance: Scaling Multi-Agent LLM Serving via Collective KV Cache Sharing

Reference 10

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source=pdf_text observed=2026-08-06T23:49:13.653093Z digest=sha256:bc3d98369d85b0c12d69c2491e5c4dc6e7eb60825d1025d67102a986959387ff

Observation 30d62a54-c948-4a39-83ee-f3513d0d529a · outbound

This paper cites Murakkab: Resource-Efficient Agentic Workflow Orchestration in Cloud Platforms,.

Architectural Implications of Agentic AI Workflows Murakkab: Resource-Efficient Agentic Workflow Orchestration in Cloud Platforms,

Reference 11

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:13.760786Z digest=sha256:e70917ccb038741eb2fc49d519b34778f6ae32fb647ac6898916d465645cad51

Observation 197b6526-dfe6-4557-815e-44650b2b51cc · outbound

This paper cites ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs,.

Architectural Implications of Agentic AI Workflows ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:13.842989Z digest=sha256:00ca859db40e5c857910e5f924c6d14cd3546ef0b3a35614df9699f1fd6c2c23

Observation 1189ad3b-1677-4c09-b5f7-a9d8fc20f03e · outbound

This paper cites Barbarians at the Gate: How AI is Upending Systems Research,.

Architectural Implications of Agentic AI Workflows Barbarians at the Gate: How AI is Upending Systems Research,

Reference 13

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source=pdf_text observed=2026-08-06T23:49:13.944332Z digest=sha256:6d98a91ed5d47310af03a9c7d946580abc752238e438425122ab3e0933773da4

Observation 911edca2-892d-4e08-9161-4d1ffb735d28 · outbound

This paper cites Fast and Flexible Multi-Agent Automation Framework,.

Architectural Implications of Agentic AI Workflows Fast and Flexible Multi-Agent Automation Framework,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.076391Z digest=sha256:4f5e77071882001d0115a42ea2503d309d19f2639dea7e7d214dd9922ce319cf

Observation 4396031c-14ca-46d0-8fa1-be74824ead5e · outbound

This paper cites RPCValet: NI-Driven Tail- Aware Balancing ofµs-Scale RPCs,.

Architectural Implications of Agentic AI Workflows RPCValet: NI-Driven Tail- Aware Balancing ofµs-Scale RPCs,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.203411Z digest=sha256:4a1ce04e54bc32103d7c85aa49ef0ae1a12b79dcea45e0d10c8754b6f435c6e9

Observation b6c2d14a-2e06-4ec8-bf64-4c0fcd056811 · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

Architectural Implications of Agentic AI Workflows FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 16

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source=pdf_text observed=2026-08-06T23:49:14.340088Z digest=sha256:8a62f7905a88ea29c74fdc00b889a94a10473ba9aee001d2ac828c9eb05a7e38

Observation 9130904a-e6a2-4fd4-804c-39153da9dcd8 · outbound

This paper cites Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing,.

Architectural Implications of Agentic AI Workflows Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.420336Z digest=sha256:1632cac88e12c415952b5b8eb19262cc883bcb75edcffb3e68c969e5db3f3140

Observation eb86c7d3-6837-417f-ad3f-00252b8914f8 · outbound

This paper cites Agentic AI Market Size,.

Architectural Implications of Agentic AI Workflows Agentic AI Market Size,

Reference 18

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.540618Z digest=sha256:fbb20aab09060a3295dde2fb3ff8a64f5d1f95920da7073080e4a48868b011b1

Observation 85519b8f-365a-41d2-a371-b4a20065f966 · outbound

This paper cites Agentic AI Requires More CPUs,.

Architectural Implications of Agentic AI Workflows Agentic AI Requires More CPUs,

Reference 19

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.676257Z digest=sha256:8d27644eaf22769b82e0a0bdb59aa9d854eafead17462419055fb9e223c74444

Observation 27289df9-49e4-430e-ad59-7a9da8289ef7 · outbound

This paper cites Memory-Harvesting VMs in Cloud Platforms,.

Architectural Implications of Agentic AI Workflows Memory-Harvesting VMs in Cloud Platforms,

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.798494Z digest=sha256:8f31c5315ae4d60726d16a905906f702ef1f1e3d46d6ee57c28bea338680f695

Observation b795c667-e3b4-4208-976b-31b642e86117 · outbound

This paper cites An Open-Source Bench- mark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems,.

Architectural Implications of Agentic AI Workflows An Open-Source Bench- mark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems,

Reference 21

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:14.924370Z digest=sha256:df8bb87be25425255f35d3a9c3575cd70b8bb548282322292d497576e7fc4a63

Observation 4dad666b-45b8-4513-90c0-fd614ee8287e · outbound

This paper cites The world’s most widely adopted AI developer tool,.

Architectural Implications of Agentic AI Workflows The world’s most widely adopted AI developer tool,

Reference 22

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:15.073545Z digest=sha256:78164b96145f156da3d82423eb694cba010fb5496c147d1f45cc227fffd0a9b4

Observation b153d9b8-3f39-473d-b0a7-8bc0e25eada4 · outbound

This paper cites Acceler- ating scientific discovery with co-scientist,.

Architectural Implications of Agentic AI Workflows Acceler- ating scientific discovery with co-scientist,

Reference 23

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:15.178151Z digest=sha256:2d80593d6596639b0e51ecdf8207384195e5947324fe221afacdf6b8551177cc

Observation 0f3e95a3-0394-482f-a636-41f967372bd6 · outbound

This paper cites The Architectural Implications of Facebook’s DNN-Based Personalized Rec- ommendation,.

Architectural Implications of Agentic AI Workflows The Architectural Implications of Facebook’s DNN-Based Personalized Rec- ommendation,

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:15.305536Z digest=sha256:6c643bb18cb69bf750fdcc84b1a1507774323b07b34f62180858a82b4a7d39fe

Observation bced1a85-1a41-4de4-848f-f126541dc7e4 · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

Architectural Implications of Agentic AI Workflows MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 25

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source=pdf_text observed=2026-08-06T23:49:15.427271Z digest=sha256:6235ac2db8cf23f9f44d4d15833111adfe058130fddbe7594e8e35edbb9bd13d

Observation 37c71dc2-58c2-4409-866f-41579c5d1722 · outbound

This paper cites OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation.

Architectural Implications of Agentic AI Workflows OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Reference 26

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source=pdf_text observed=2026-08-06T23:49:15.590641Z digest=sha256:1410636110d1e10381a38710fb5f799117bb9160d07fe58d2169e5145fe7acc4

Observation 7adac83d-1e38-43d7-b3d1-da7cf9d9e9b8 · outbound

This paper cites The nanoPU: A Nanosecond Network Stack for Data- centers,.

Architectural Implications of Agentic AI Workflows The nanoPU: A Nanosecond Network Stack for Data- centers,

Reference 27

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:15.753079Z digest=sha256:d0cd0a72af058520f28f121b343254e8536bbb62abf955e8ea2ce9406fb7832f

Observation d49cf6df-bce5-4c14-a20f-9f1a63263f6a · outbound

This paper cites What is a multi-agent system?.

Architectural Implications of Agentic AI Workflows What is a multi-agent system?

Reference 28

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:15.862945Z digest=sha256:0446c343f622151436ab24bb23f8f4878e041ee0fab3a920b7b01bf5a949cce5

Observation af5be4d2-e458-4a21-9232-c6ce0e6ee64e · outbound

This paper cites Agentic AI in enterprise workflow automation,.

Architectural Implications of Agentic AI Workflows Agentic AI in enterprise workflow automation,

Reference 29

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:15.981433Z digest=sha256:b6ea067613098c459e77076e6c09fff061292cfa93ab92d17e4973c5a39886eb

Observation 64ba100f-d659-4559-a014-86f41c9038fe · outbound

This paper cites Profiling a warehouse-scale computer,.

Architectural Implications of Agentic AI Workflows Profiling a warehouse-scale computer,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:16.090630Z digest=sha256:d5caabd464cea1b279340920a32fa3fe9ed8a747e9e35ef7cf618e18dfd86dc1

Observation f7ddc9fa-6495-4e7a-8a60-fe9fab7e3b01 · outbound

This paper cites ThunderAgent: A Simple, Fast and Program-Aware Agentic Inference System.

Architectural Implications of Agentic AI Workflows ThunderAgent: A Simple, Fast and Program-Aware Agentic Inference System

Reference 31

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source=pdf_text observed=2026-08-06T23:49:16.197694Z digest=sha256:51498468f1cb801bda4f9eb9d89cff8ebd5e10fb7c62f6b3aa664d10abb5a3f4

Observation 9a784cae-4909-4c61-88cf-9ba1739bcc7c · outbound

This paper cites A Hardware Accelerator for Protocol Buffers,.

Architectural Implications of Agentic AI Workflows A Hardware Accelerator for Protocol Buffers,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:16.288481Z digest=sha256:164ea123c25a9ca15b0acf3046ec2acc045aa7e545508969b6007b7072445547

Observation 4e64cd99-7ebd-4441-b584-f8d805efc52a · outbound

This paper cites CDPU: Co-designing Compression and Decom- pression Processing Units for Hyperscale Systems,.

Architectural Implications of Agentic AI Workflows CDPU: Co-designing Compression and Decom- pression Processing Units for Hyperscale Systems,

Reference 33

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raw_fallback, observed 2026-08-06T23:49:27.801268Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:16.389584Z digest=sha256:8df0bcfabfe170f9f146c8ae57d6eb7d60d0de946cb8dc382a4369e62ca6cea7

Observation 32ee5653-6dee-4658-9f13-79c0f1a3cd43 · outbound

This paper cites MorphCore: An Energy-Efficient Microarchitecture for High Performance ILP and High Throughput TLP,.

Architectural Implications of Agentic AI Workflows MorphCore: An Energy-Efficient Microarchitecture for High Performance ILP and High Throughput TLP,

Reference 34

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raw_fallback, observed 2026-08-06T23:49:27.565210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:16.506907Z digest=sha256:77d01cb19a7faeaced1df112ae14533a72f0a16e69e9ba2090b07f60e5bbede8

Observation 830a6330-2c7c-4d01-9fc2-31d95a5b63fe · outbound

This paper cites LIA: A Single-GPU LLM Inference Acceleration with Cooper- ative AMX-Enabled CPU-GPU Computation and CXL Offloading,.

Architectural Implications of Agentic AI Workflows LIA: A Single-GPU LLM Inference Acceleration with Cooper- ative AMX-Enabled CPU-GPU Computation and CXL Offloading,

Reference 35

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raw_fallback, observed 2026-08-06T23:49:27.322987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:16.624746Z digest=sha256:790358ea3d41e877616c2340913b04181d66ff2cc9b1540969a26662d43b54dd

Observation b55e61dc-382e-45b2-9e26-fb3b920a449d · outbound

This paper cites The cost of dynamic reasoning: Demystifying AI agents and test-time scaling from an AI infrastructure perspective,.

Architectural Implications of Agentic AI Workflows The cost of dynamic reasoning: Demystifying AI agents and test-time scaling from an AI infrastructure perspective,

Reference 36

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no resolver link, observed 2026-08-06T23:49:16.769997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:16.769997Z digest=sha256:6ea2ceb8dbd2f9862bba989aae1240a919079492e8d22d002cd994a7ed4a978c

Observation 8a1ee723-225d-4a70-9976-8cb12f70feed · outbound

This paper cites PhaseWeave: Phase-Aware Execution on Heterogeneous Chiplet Architectures for Dat- acenters,.

Architectural Implications of Agentic AI Workflows PhaseWeave: Phase-Aware Execution on Heterogeneous Chiplet Architectures for Dat- acenters,

Reference 37

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raw_fallback, observed 2026-08-06T23:49:27.162515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:16.926199Z digest=sha256:b4b84e570fbb4f1533579268bd3cfb03503c95ff76679214202d6671e97f139c

Observation 752164a1-e484-4103-bac6-5244d770ba3a · outbound

This paper cites Single-ISA heterogeneous multi-core architectures for multithreaded workload performance,.

Architectural Implications of Agentic AI Workflows Single-ISA heterogeneous multi-core architectures for multithreaded workload performance,

Reference 38

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raw_fallback, observed 2026-08-06T23:49:27.020117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.044906Z digest=sha256:a9ae13150c7e4204678b75e7571f23071e88d9e1e25475eefc6698d1790c5539

Observation 1f90404d-883b-41d7-8ccb-d9e71b91720e · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention,.

Architectural Implications of Agentic AI Workflows Efficient Memory Management for Large Language Model Serving with PagedAttention,

Reference 39

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raw_fallback, observed 2026-08-06T23:49:26.857514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.179748Z digest=sha256:c3fa70f7b0c527df0b63f6f3b06ed43f4cf0ba6a0bb00b7be4dc4740b928c3c8

Observation 774206fc-564c-41dc-89b7-e35d77af3d8b · outbound

This paper cites langgraph: Low-level orchestration framework for building stateful agents,.

Architectural Implications of Agentic AI Workflows langgraph: Low-level orchestration framework for building stateful agents,

Reference 40

Resolution
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raw_fallback, observed 2026-08-06T23:49:26.704886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.308281Z digest=sha256:411c25ebfc5429b6e841ae7826591dfa235e135951f4cb29f35acaf1609f99eb

Observation 3fe0ba39-5a73-495c-b0aa-74966d901bcb · outbound

This paper cites AiF: Accelerating On-Device LLM Inference Using In-Flash Processing,.

Architectural Implications of Agentic AI Workflows AiF: Accelerating On-Device LLM Inference Using In-Flash Processing,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:26.585067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.484727Z digest=sha256:e47bf6da3623473248f7bc8ba455737c5702741276730cc264a6c2eae979f17c

Observation b41edb0e-9f71-469d-a824-e7522ec94aa1 · outbound

This paper cites H2-LLM: Hardware-Dataflow Co- Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference,.

Architectural Implications of Agentic AI Workflows H2-LLM: Hardware-Dataflow Co- Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference,

Reference 42

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raw_fallback, observed 2026-08-06T23:49:26.487240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.598440Z digest=sha256:6e9f526c0f16a26672b53ce4d9e87c70cf6a390d2003a9c61a15509f388d9cf0

Observation 11e87be3-eb61-45b1-8ec6-697cddae1004 · outbound

This paper cites KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta.

Architectural Implications of Agentic AI Workflows KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta

Reference 43

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no resolver link, observed 2026-08-06T23:49:17.692396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:17.692396Z digest=sha256:41ef18f0b9b5b40712b67d526739df1c74b651ffb6951093105e979d6543c742

Observation c10dd264-5b77-4906-ba3d-1b34e37c5427 · outbound

This paper cites Agentix: An Efficient Serving Engine for LLM Agents as General Programs,.

Architectural Implications of Agentic AI Workflows Agentix: An Efficient Serving Engine for LLM Agents as General Programs,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:26.352591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.802965Z digest=sha256:18c18ad4352462f0d44ce9b228bee520ebfb57a1df0e3ce3552c250ab5685271

Observation 1b4b5619-ea75-429e-900e-8af51f30dab6 · outbound

This paper cites Decentralized Multi-Agent Systems with Shared Context,.

Architectural Implications of Agentic AI Workflows Decentralized Multi-Agent Systems with Shared Context,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:26.199381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:17.928828Z digest=sha256:52eb269c9baadb65bb1b3258f2864c204c4f30779b72d72dfcdb29a7ba9d1cf2

Observation 2ed61c70-fc4c-4380-9cb3-7ed00aa76d2a · outbound

This paper cites GAIA: a benchmark for General AI Assistants.

Architectural Implications of Agentic AI Workflows GAIA: a benchmark for General AI Assistants

Reference 46

Resolution
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no resolver link, observed 2026-08-06T23:49:18.076094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:18.076094Z digest=sha256:c50d732018c8d2ffae7d73c88cdbbd5cf341b656f69e399863c4f65f510ba575

Observation e66ee86f-e1d9-489e-87df-ca7f6d531d0b · outbound

This paper cites SpotServe: Serving Generative Large Language Models on Preemptible Instances,.

Architectural Implications of Agentic AI Workflows SpotServe: Serving Generative Large Language Models on Preemptible Instances,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:26.058182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:18.222260Z digest=sha256:dd730418022feb3cb878652e223d34dfaf643569241e81747ade23ab882e491c

Observation 0a1bd0ca-f46b-445a-bc73-eb21d5302afd · outbound

This paper cites AutoGen: A programming framework for agentic AI,.

Architectural Implications of Agentic AI Workflows AutoGen: A programming framework for agentic AI,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.919319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:18.340202Z digest=sha256:fa7a57b4988a929d97bd66454c4fc796881118c0a32b3838908497d7504ec564

Observation 21424f95-f961-4d2e-af5e-118d4cf3375f · outbound

This paper cites Enhancing Server Efficiency in the Face of Killer Microseconds,.

Architectural Implications of Agentic AI Workflows Enhancing Server Efficiency in the Face of Killer Microseconds,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.809836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:18.489631Z digest=sha256:0095ebec4643745e392662429d575fda60b9f107bbe2061a68ff019c87be704f

Observation a9cbded6-85de-4d88-aa14-d8169263dc03 · outbound

This paper cites AlphaEvolve: A coding agent for scientific and algorithmic discovery.

Architectural Implications of Agentic AI Workflows AlphaEvolve: A coding agent for scientific and algorithmic discovery

Reference 50

Resolution
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no resolver link, observed 2026-08-06T23:49:18.646754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:18.646754Z digest=sha256:2214faf2ac67ec1962edd79972ec6297363ec4810360c8f328da4f004baefce0

Observation 57ed4cdf-4292-44ba-bfbe-6dd2c5a2b9f9 · outbound

This paper cites TensorRT-LLM’s Documentation,.

Architectural Implications of Agentic AI Workflows TensorRT-LLM’s Documentation,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.654300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:18.769902Z digest=sha256:8d41bcda8fd8fd5b26699cbd23eedfc2963c32f6dbc74a2acd8453c4a03ee86f

Observation 5e8fff49-82f6-466b-9d4d-4d764c4ccfbf · outbound

This paper cites Web Search,.

Architectural Implications of Agentic AI Workflows Web Search,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.536981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:18.890642Z digest=sha256:3694d1b4820ff0b7dbb394fd547c7e224f845092994e8eaf578cc8de5cb23207

Observation cea3102a-95ad-42bd-bbf5-679d7fa369ac · outbound

This paper cites Splitwise: Efficient generative LLM inference using phase splitting,.

Architectural Implications of Agentic AI Workflows Splitwise: Efficient generative LLM inference using phase splitting,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.394508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.031890Z digest=sha256:f29329e2cc08d507ebe7a591c5af79b9894e4924becec2d580d60be149b5a536

Observation 71276bda-e1ad-4c11-806a-cc8993925275 · outbound

This paper cites VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generation.

Architectural Implications of Agentic AI Workflows VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generation

Reference 54

Resolution
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no resolver link, observed 2026-08-06T23:49:19.162016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.162016Z digest=sha256:f7c4ace36717a077b321b0722efa95c716fde0b4630a7170fd1105ecf03eb25e

Observation 3dceed43-ac5d-432d-bfce-96e6fb6e2dd6 · outbound

This paper cites Enterprise deep research: Steerable multi-agent deep research for enterprise analytics,.

Architectural Implications of Agentic AI Workflows Enterprise deep research: Steerable multi-agent deep research for enterprise analytics,

Reference 55

Resolution
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no resolver link, observed 2026-08-06T23:49:19.235665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.235665Z digest=sha256:76cbd2ea5a1d99d9329e52346227be78d784aa9b2a3a920ec79b9aacb5089e8c

Observation 1328a797-0e4c-4b31-87ab-865b6570ea39 · outbound

This paper cites CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended Discovery.

Architectural Implications of Agentic AI Workflows CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended Discovery

Reference 56

Resolution
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no resolver link, observed 2026-08-06T23:49:19.295366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.295366Z digest=sha256:5be5e08be57109d356840f6ef1bb33017bec5a7f85fa92abd2d5c79508f76d51

Observation a587600f-165d-492b-a945-6aa21a34b053 · outbound

This paper cites Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective.

Architectural Implications of Agentic AI Workflows Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective

Reference 57

Resolution
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no resolver link, observed 2026-08-06T23:49:19.348281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.348281Z digest=sha256:558c5c4ffc29f81e266fc5886169410e2ac15e0d1d2b132455e572067c3aa5a2

Observation 9e02c260-9969-4b96-aa12-b49e2ad7241d · outbound

This paper cites AOrchestra: Automating Sub- Agent Creation for Agentic Orchestration,.

Architectural Implications of Agentic AI Workflows AOrchestra: Automating Sub- Agent Creation for Agentic Orchestration,

Reference 58

Resolution
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no resolver link, observed 2026-08-06T23:49:19.427377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.427377Z digest=sha256:9d138ca25c453120fdc678adf23c16f5c7277b1d6bc5a8235f413e76108b144c

Observation bedff36f-ee3e-41dc-a7c0-21e90703e3a6 · outbound

This paper cites Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning,.

Architectural Implications of Agentic AI Workflows Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning,

Reference 59

Resolution
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no resolver link, observed 2026-08-06T23:49:19.494760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.494760Z digest=sha256:0a8cc24d51b8760b4773902bb4c4730b8cdd9286012624538638fd9997073e8e

Observation eb193f5a-33c2-4a12-ba2d-d9f52b57761d · outbound

This paper cites Accelerometer: Understanding Accel- eration Opportunities for Data Center Overheads at Hyperscale,.

Architectural Implications of Agentic AI Workflows Accelerometer: Understanding Accel- eration Opportunities for Data Center Overheads at Hyperscale,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.259470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.556695Z digest=sha256:b721f0dbcfcb662359489ef4032b0f3a1f98a910bd3ed61d12c54fa0c8e7984f

Observation b2dfad12-3f73-4e36-8b58-0c1ce861c093 · outbound

This paper cites Mosaic: Harnessing the Micro-Architectural Resources of Servers in Serverless Environments,.

Architectural Implications of Agentic AI Workflows Mosaic: Harnessing the Micro-Architectural Resources of Servers in Serverless Environments,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:25.115384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.648108Z digest=sha256:72f4f6c89e93528f49fe73aaabb062faf93637716c211c692a1f4c2ab9bb7492

Observation 6d649949-4c3e-4494-be0b-a360628e3299 · outbound

This paper cites AccelFlow: Orchestrating an On-Package Ensemble of Fine-Grained Accelerators for Microservices,.

Architectural Implications of Agentic AI Workflows AccelFlow: Orchestrating an On-Package Ensemble of Fine-Grained Accelerators for Microservices,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.968100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.740414Z digest=sha256:764bb5ea950173f6a99789d9d3a11555cfb29916dbefd01ddc14d7c1d72bab64

Observation f93c6042-724e-4438-8ebb-1104055eeaa5 · outbound

This paper cites µManycore: A Cloud-Native CPU for Tail at Scale,.

Architectural Implications of Agentic AI Workflows µManycore: A Cloud-Native CPU for Tail at Scale,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.835756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.804868Z digest=sha256:8afcc444fa4f1a1657ec6e3ad079c6d75e60756c9f98905ac5447de96e80938e

Observation 6dbbc2ca-ede1-4639-a456-82a410a330b8 · outbound

This paper cites HardHarvest: Hardware-Supported Core Harvesting for Microservices,.

Architectural Implications of Agentic AI Workflows HardHarvest: Hardware-Supported Core Harvesting for Microservices,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.688942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.877516Z digest=sha256:106d8763fb2cffc681fdd0c7d18583a568b16fb9bbcfa83a8eddfb0f744162f5

Observation 67fc37b8-335d-453f-96b0-94a6ade9ddca · outbound

This paper cites ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration,.

Architectural Implications of Agentic AI Workflows ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration,

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T23:49:19.933806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:19.933806Z digest=sha256:4ee21827bb76edacb9fbedc8c8debab0576ffd0a0ed659d86bc7f3857f616ccd

Observation 738eeb80-bde8-4495-9549-b0c1be0ec32c · outbound

This paper cites DCPerf: An Open-Source, Battle-Tested Performance Benchmark Suite for Dat- acenter Workloads,.

Architectural Implications of Agentic AI Workflows DCPerf: An Open-Source, Battle-Tested Performance Benchmark Suite for Dat- acenter Workloads,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.514107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:19.987268Z digest=sha256:bb944ae450afd73f180fc9d17e29a521fe1384de30c48575b03a92657d025f3e

Observation a7daaa39-ab63-4c10-8d1d-ad31e4c27095 · outbound

This paper cites Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling.

Architectural Implications of Agentic AI Workflows Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling

Reference 67

Resolution
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no resolver link, observed 2026-08-06T23:49:20.030415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:20.030415Z digest=sha256:4ebd23a8171b8d8f99a2d11ac4e88bfd984ef2859e208d3d6d707cc6181d8128

Observation d0e6e265-d6dc-4011-b39a-e3dd7390e94c · outbound

This paper cites Attention is All You Need,.

Architectural Implications of Agentic AI Workflows Attention is All You Need,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.357631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.108200Z digest=sha256:c6dc37a29969e703da0a9de8894df22babbce9a9f86b836f1eecf84eb1ef0c5e

Observation b241b6e3-d643-4195-a866-ff4b98ca2bcf · outbound

This paper cites SmartHarvest: Har- vesting Idle CPUs Safely and Efficiently in the Cloud,.

Architectural Implications of Agentic AI Workflows SmartHarvest: Har- vesting Idle CPUs Safely and Efficiently in the Cloud,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.169218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.173555Z digest=sha256:17c15b4c1ad008376f83deebdf9526221d55fe64629226cf626f78902da2e7e7

Observation 355844c6-0d46-4f67-95a6-613f1a07a3c1 · outbound

This paper cites WSC-LLM: Efficient LLM Service and Architecture Co- exploration for Wafer-scale Chips,.

Architectural Implications of Agentic AI Workflows WSC-LLM: Efficient LLM Service and Architecture Co- exploration for Wafer-scale Chips,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:49:24.027455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.227654Z digest=sha256:0d6a9d0c7926df2b8033e4e6804c98601d8945a9329aa7f96feeb7e5c5ecef22

Observation be198d5f-6e14-49f1-b8a0-a4ca012b7f51 · outbound

This paper cites SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering.

Architectural Implications of Agentic AI Workflows SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

Reference 71

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no resolver link, observed 2026-08-06T23:49:20.282010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:20.282010Z digest=sha256:34f63f8761ba6f3626be55525be1cc2cb00501c073c9679f0b4ced08b031df5a

Observation 3dc734a3-bb08-40cb-ad42-c524e84535d3 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Architectural Implications of Agentic AI Workflows ReAct: Synergizing Reasoning and Acting in Language Models

Reference 72

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no resolver link, observed 2026-08-06T23:49:20.370827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:20.370827Z digest=sha256:5b98db71c790d1ffb65832c1996473535612fdc43f5ee7cc2786b703c2ca7e40

Observation b3f937ad-014c-43db-a0f5-9054ece18a2b · outbound

This paper cites Speculative Actions: A Lossless Framework for Faster Agentic Systems.

Architectural Implications of Agentic AI Workflows Speculative Actions: A Lossless Framework for Faster Agentic Systems

Reference 73

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no resolver link, observed 2026-08-06T23:49:20.435352Z

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source=pdf_text observed=2026-08-06T23:49:20.435352Z digest=sha256:ccf0b95de2b8d0c055707dc77df1b126fd8dcd784cb39042c00e031536a30841

Observation ded9fdac-c96c-4cee-8208-0ab256cad5a3 · outbound

This paper cites Orca: A Distributed Serving System for Transformer-Based Generative Models,.

Architectural Implications of Agentic AI Workflows Orca: A Distributed Serving System for Transformer-Based Generative Models,

Reference 74

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.882612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.512503Z digest=sha256:24bb8e6661e70dc1dff7f5e6a8bba680138a92841cac7f624a67c6a47b33fe24

Observation 11b95232-9949-4d7c-a9e7-4d44e760fde8 · outbound

This paper cites Pythia: Exploiting Workflow Predictability for Efficient Agent-Native LLM Serving.

Architectural Implications of Agentic AI Workflows Pythia: Exploiting Workflow Predictability for Efficient Agent-Native LLM Serving

Reference 75

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no resolver link, observed 2026-08-06T23:49:20.607618Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T23:49:20.607618Z digest=sha256:e591e90ac28ef8eca8311de4b84c7d1c35be51d2898a74eaf383658c7f24eecb

Observation e3f0d661-45ac-4e7c-812a-399762505f7a · outbound

This paper cites Agentic AI Workload Characteristics.

Architectural Implications of Agentic AI Workflows Agentic AI Workload Characteristics

Reference 76

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verified exact
local_arxiv, observed 2026-08-06T23:49:21.757892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.692099Z digest=sha256:dac03fc02ba3a47ad052543a241135af343c7df8424be38b2716a1aa7dacca66

Observation 194a4ae8-fd59-4179-b637-435a57aa65e6 · outbound

This paper cites AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization.

Architectural Implications of Agentic AI Workflows AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization

Reference 77

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no resolver link, observed 2026-08-06T23:49:20.763980Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T23:49:20.763980Z digest=sha256:c742ef88420064f88f249fb8535ce77518c17ca50f7e053b89e1d6a45455de7a

Observation 57eb309a-8543-4e1a-a848-df11278ad04e · outbound

This paper cites Faster and Cheaper Serverless Computing on Harvested Resources,.

Architectural Implications of Agentic AI Workflows Faster and Cheaper Serverless Computing on Harvested Resources,

Reference 78

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.731313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.871762Z digest=sha256:7b537c1790212ec424185adb10c9baa67d5b9acb98629caf6d0a6cbfa82a3178

Observation c093365b-2ceb-48c4-9355-9d96df357b70 · outbound

This paper cites History-Based Harvesting of Spare Cycles and Storage in Large-Scale Datacenters,.

Architectural Implications of Agentic AI Workflows History-Based Harvesting of Spare Cycles and Storage in Large-Scale Datacenters,

Reference 79

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.606074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.932161Z digest=sha256:8f0647962d08ef4c6adf62b9b9fa13fe729a3f797c9fd557053207a7b7efda15

Observation 4988c439-1eab-41ad-ab9d-61e9041cf897 · outbound

This paper cites ALTOCUMULUS: Scalable Scheduling for Nanosecond-Scale Remote Procedure Calls,.

Architectural Implications of Agentic AI Workflows ALTOCUMULUS: Scalable Scheduling for Nanosecond-Scale Remote Procedure Calls,

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.491493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:20.999787Z digest=sha256:9817c08bbd9411f37b39c48b963198b9d24c01539b8f6059e47cc06c75f9f879

Observation 8d6a3c32-0785-4898-96c3-c87955e1fb0d · outbound

This paper cites ALISA: Accelerating Large Lan- guage Model Inference via Sparsity-Aware KV Caching,.

Architectural Implications of Agentic AI Workflows ALISA: Accelerating Large Lan- guage Model Inference via Sparsity-Aware KV Caching,

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.341827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:21.077794Z digest=sha256:c5bc47ea7cdda74a6865ac1b7d403c8173923c65fabacf0520dd794174a57f4f

Observation a357c2a9-af11-44b1-ad78-c109453dd047 · outbound

This paper cites MAGE: A Multi-Agent Engine for Automated RTL Code Generation.

Architectural Implications of Agentic AI Workflows MAGE: A Multi-Agent Engine for Automated RTL Code Generation

Reference 82

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no resolver link, observed 2026-08-06T23:49:21.149678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:21.149678Z digest=sha256:527a8864b09316ee7112ea327a3dac6ee6d486ae027362c0cb9f4fc6c235a483

Observation 668652c2-9e65-4363-8e25-2b6060b73a8b · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs,.

Architectural Implications of Agentic AI Workflows SGLang: Efficient Execution of Structured Language Model Programs,

Reference 83

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.186858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:21.213607Z digest=sha256:af00cf9066ab311e5eec2bba081ebe064aed17df3a955cdc39e74ee513a84538

Observation 1710c802-7353-46b8-bfbc-1b289696f11a · outbound

This paper cites PetS: A unified framework for parameter-efficient transformers serving,.

Architectural Implications of Agentic AI Workflows PetS: A unified framework for parameter-efficient transformers serving,

Reference 84

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verified fuzzy
raw_fallback, observed 2026-08-06T23:49:23.017873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:49:21.427575Z digest=sha256:dfcd0ac56d96c6d097eccc309c6ddcc150d83a2aaaa6b811e1607e7a53ca2a1b

Observation 13afa92a-cb0d-4485-ab58-6a1b28d991b0 · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs.

Architectural Implications of Agentic AI Workflows SGLang: Efficient Execution of Structured Language Model Programs

Reference 2024

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no resolver link, observed 2026-08-06T23:49:21.307084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:21.307084Z digest=sha256:d5e2d4aeeb5cf61ac940f528cb08ef2cc9a757964c1cf16149ce7e50231316a4

Observation dc1222b4-c4f8-4104-8ca3-37be6ebfbe42 · outbound

This paper cites Available: https://www.arm.com/technologies/big-little.

Architectural Implications of Agentic AI Workflows Available: https://www.arm.com/technologies/big-little

Reference 2025

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no resolver link, observed 2026-08-06T23:49:13.093850Z

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source=pdf_text observed=2026-08-06T23:49:13.093850Z digest=sha256:48d7798d2393ce2655b33f82564f0c3726c3242b439a15aa09df6eff9d9bfee7

Pith citing papers

No inbound Pith citation observations are available.