Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-12T01:16:50.927415Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 0 inbound Pith citation observations for arXiv:2607.03601.
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 2026-07-12T01:16:50.927415Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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
77 of 77 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8ae5287f-8ec0-4ac7-ab20-97416684f8a8 · outbound
ArchEval: Measuring AI Agents as Computer Architects Performance Prediction for Large Systems via Text-to-Text Regression
Reference 1
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Observation 7a1c636e-674d-4b6a-a822-7d3557a0d7fe · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 2
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Observation 098a6ffe-46b5-4b1c-ad1a-d271966cb42b · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 3
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Observation dd93eef1-d15b-496f-980f-69bc4b5bdecb · outbound
ArchEval: Measuring AI Agents as Computer Architects Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization
Reference 4
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Observation bea065a9-058d-4b14-b860-be5bc66769ee · outbound
ArchEval: Measuring AI Agents as Computer Architects Chip-Chat: Challenges and Opportunities in Conversational Hardware Design
Reference 5
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Observation 8f6e6545-dd16-4a04-aad6-2082b41e538d · outbound
ArchEval: Measuring AI Agents as Computer Architects Kistowski
Reference 6
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Observation a3dbd7b0-885e-48fa-b7c3-25fe26ab273b · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 7
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Observation 5bd4612d-212c-4cec-a388-025d80acf4dd · outbound
ArchEval: Measuring AI Agents as Computer Architects An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 8
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Observation a3c8cd15-06c9-4b23-aa4f-ac488e5ce86d · outbound
ArchEval: Measuring AI Agents as Computer Architects Compositional Generative Modeling: A Single Model is Not All You Need
Reference 9
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Observation 1c62a20a-a917-4d83-8b86-9c524b9cbb76 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 10
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Observation 49faacec-cdce-4644-a314-0061da4a81a6 · outbound
ArchEval: Measuring AI Agents as Computer Architects The Championship Simulator: Architectural Simulation for Education and Competition
Reference 11
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Observation 800a6e52-008c-45fe-8ad3-2fd7120f7a21 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 12
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Observation be3cdc0d-e744-44d1-b81f-4d125d066aaa · outbound
ArchEval: Measuring AI Agents as Computer Architects Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Reference 13
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Observation 0451b42d-f858-48e3-a3c1-170e44da9fd7 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 14
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Observation 50b805c0-af55-4325-990e-16fa5eddd188 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 15
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Observation eb2c444c-794f-4267-85e8-ae1366634c74 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 16
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Observation 5ec7eccd-f664-4f90-aedf-6adcbf74213f · outbound
ArchEval: Measuring AI Agents as Computer Architects MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
Reference 17
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Observation 6359306c-da03-4e50-b7cc-ca8b9e135d86 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 18
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Observation f1b38829-064d-44dd-a764-72ef87f5c923 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 19
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Observation 5169574a-a4ca-4956-9e7f-fce33a001830 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 20
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Observation 8ce9bd64-5b65-4190-b89c-5e4439003c46 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 21
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Observation 62febaf4-af1f-498f-85c4-3a1ca4f14ace · outbound
ArchEval: Measuring AI Agents as Computer Architects Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration
Reference 22
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Observation 7dab6982-29a2-4a85-9de7-2a7b14849ab3 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 23
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Observation baee5bd1-60f0-4727-ab3e-316b4f6230d5 · outbound
ArchEval: Measuring AI Agents as Computer Architects In2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO)
Reference 24
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Observation 1db8d54e-c573-40ca-9fc6-d5633ad26fbe · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 25
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Observation 7f155ebc-587f-408a-93c8-15eba5eedaaf · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 26
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Observation fc75ad21-f73f-4964-b454-e5be4aec26b9 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 27
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Observation 60969956-7511-4124-8465-1829f3a0415f · outbound
ArchEval: Measuring AI Agents as Computer Architects VerilogEval: Evaluating Large Language Models for Verilog Code Generation
Reference 28
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Observation 5e19bfea-0437-473c-8d2b-e9a4c1e01820 · outbound
ArchEval: Measuring AI Agents as Computer Architects General-Reasoner: Advancing LLM Reasoning Across All Domains
Reference 29
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Observation e2e9f587-c48e-4be2-af48-476511ae04fe · outbound
ArchEval: Measuring AI Agents as Computer Architects 1993.Combining Branch Predictors
Reference 30
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Observation c80ff65f-fcd1-4905-a7ba-8c15e9025b36 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 31
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Observation 3d5ca5d6-cd04-4b96-b681-bc118cc8c726 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 32
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Observation dcb20339-c1cb-4b10-a3bc-f081d2781dd2 · outbound
ArchEval: Measuring AI Agents as Computer Architects Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Reference 33
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Observation 00b1324f-21be-480a-8685-74d0aa3d9fab · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 34
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Observation 4ca49435-4178-4eae-8b6d-38cc3f9e8455 · outbound
ArchEval: Measuring AI Agents as Computer Architects KernelBench: Can LLMs Write Efficient GPU Kernels?
Reference 35
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Observation bb3598fc-5f27-4aed-9a1f-544ee757a23e · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 36
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Observation 45359745-1be5-4cf3-9d38-4b34af838c1d · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 37
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Observation 4c266c25-5d13-4b8b-880e-c53d95c66f81 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 38
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Observation 3f4734c6-3ec6-4033-ab62-a0322c18d90f · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 39
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Observation 8756bc80-f968-4c8f-a1d2-904a1a1da59b · outbound
ArchEval: Measuring AI Agents as Computer Architects Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions
Reference 40
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Observation c08fed90-d824-4e70-811c-83adb364301d · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 41
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Observation 4693cb89-1fb7-4d0f-be7d-81206c9e09a5 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 42
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Observation 1a7a5af9-1595-458b-8a3b-ec87fcc05765 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 43
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Observation 7df266ad-d19e-4294-9281-5f27940c90d0 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 44
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Observation 2764c245-bd25-4bf7-940d-669c596679ec · outbound
ArchEval: Measuring AI Agents as Computer Architects AutoChip: Automating HDL Generation Using LLM Feedback
Reference 45
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Observation f19eb196-3d1e-4226-aee0-eeef3a679815 · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 46
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Observation dc7b7c1b-6e4e-43c9-a741-a66fbba81484 · outbound
ArchEval: Measuring AI Agents as Computer Architects AgentDSE: Reasoning-Augmented Architectural Design Space Exploration
Reference 47
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Observation de71bab6-04ec-4320-93dc-045b55e8d7ae · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 48
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Observation 9beda241-b065-4d7f-b0db-ff5ba305f04f · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 49
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Observation a0d35842-933d-4703-ade4-7cac914ff4ce · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 50
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Observation 1db5d6c7-ae88-4234-8d6a-4c1219a2d50a · outbound
ArchEval: Measuring AI Agents as Computer Architects SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
Reference 51
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Observation f8663cfd-75fb-42d0-8bda-d2b42f5110ea · outbound
ArchEval: Measuring AI Agents as Computer Architects ProgramBench: Can Language Models Rebuild Programs From Scratch?
Reference 52
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Observation 3013305e-99e6-4f45-b642-67315f4f6ecc · outbound
ArchEval: Measuring AI Agents as Computer Architects ReAct: Synergizing Reasoning and Acting in Language Models
Reference 53
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Observation 899d1f65-40ae-4c5d-afe1-69ffdde5fe0b · outbound
ArchEval: Measuring AI Agents as Computer Architects Apollo: Transferable Architecture Exploration
Reference 54
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Observation 220371d5-9ce2-4ba8-868b-da4c7c863555 · outbound
ArchEval: Measuring AI Agents as Computer Architects LEAP: Trajectory-Level Evaluation of LLMs in Iterative Scientific Design
Reference 55
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Observation 81ae78d8-605d-43de-89d8-3306f5df948f · outbound
ArchEval: Measuring AI Agents as Computer Architects Unresolved cited work
Reference 56
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Observation 404308c3-7a66-480a-8b80-356ed612d3bd · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:3 SPEC CPU2017 traces [6] (perlbench, gcc, xalancbmk); 3M-instr warmup + 7M-instr measure
Reference 57
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Observation 45708ef8-2258-47fd-a216-00d2318caf27 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:3 SPEC CPU2017 traces (perlbench, gcc, xalancbmk); 3M + 7M instr
Reference 58
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Observation 2e7a0fc7-8b2a-4bc3-834c-1e898eedf562 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:6 SPEC CPU2017 traces (sphinx3, mcf×2, omnetpp,
Reference 59
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Observation 42ff2023-482e-439a-ba7a-5e86355d433c · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:3 memory-intensive SPEC traces (mcf, libquantum, mcf); 3M + 7M instr
Reference 60
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Observation fe61c9f9-508b-4568-8b80-95f540bbe3a5 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:3 SPEC CPU2017 traces (perlbench, gcc, xalancbmk); 3M + 7M instr
Reference 61
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Observation 0f5be66c-e41d-4792-a7ba-ab65314b20de · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:3 SPEC CPU2017 traces (mcf×2, omnetpp); 3M + 7M instr
Reference 62
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Observation f38e11a5-8e34-4015-aa9a-a1e42d7bcf4a · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:Single-CPU gem5 SE-mode workload
Reference 63
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Observation 77bf5571-718e-49ba-b63f-30dc1ca68547 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:Fixed DDR4 access trace
Reference 64
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Observation 3cfd2081-9255-464a-bbef-77294cc586ef · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:Fixed memory access trace
Reference 65
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Observation 5aa9f5b7-f5c1-44f7-ac34-572377d67006 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:All-Reduce, 8 NPUs, fixed topology + workload
Reference 66
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Observation e72afae5-66b2-4563-b281-3bf1fc48900e · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:All-Gather, 8 NPUs, fixed topology + workload
Reference 67
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Observation 57f80266-0aa1-4100-a515-45b01e2c228e · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:All-to-All, 8 NPUs, fixed topology + workload
Reference 68
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Observation 57a378f4-682a-45ad-8355-a1c42c495fde · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:All-to-All, 16 NPUs, fixed topology + workload
Reference 69
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Observation 2159e1b2-85fc-4ef3-802e-930268fb2263 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:Reduce-Scatter, 8 NPUs, fixed topology + workload
Reference 70
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Observation 7f610047-04d7-4d7b-a9bd-222e03492228 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:ViT-Base [8] (14 layers); 4 cores, each 128×128 PE array, 256 KB SRAMs, BW=10
Reference 71
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Observation 53420f04-178c-4170-98a5-d90c1065e511 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:ViT-Base [8] (14 layers); 4 cores, each 256×256 PE array, 256 KB SRAMs, BW=10
Reference 72
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Observation f179e8c3-750d-47b1-8e3e-ee41456f8817 · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:ViT-Base [8] (14 layers); 4 cores, each 64×64 PE array, 256 KB SRAMs, BW=10
Reference 73
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Observation 9a98eaef-a64c-4793-a9b9-559239fa780d · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:ResNet-50 [15] (24 unique layers) on one fixed DNN accelerator
Reference 74
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Observation e2122eda-e217-407f-b8c8-c2082fe3b5fa · outbound
ArchEval: Measuring AI Agents as Computer Architects Workload:MNSIM ReRAM CIM design point
Reference 75
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Observation add26959-3ba5-445a-bdea-402b6f4f11b4 · outbound
ArchEval: Measuring AI Agents as Computer Architects We have successfully designed
Reference 76
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Observation dcf317fd-c8fe-4399-9e0a-8dc929c3d2c0 · outbound
ArchEval: Measuring AI Agents as Computer Architects has_member
Reference 77
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No inbound Pith citation observations are available.