Paper Citation Record · LEDGER

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory

As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.02311.

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

pith.paper-citation-record.v1
2506.02311 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:31:54.751094Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

27 of 27 outbound references displayed

verified exact0
verified fuzzy24
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8bfacb1f-f2d2-46d6-92bf-348bfd472d71 · outbound

This paper cites Neuro-inspired computing chips,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Neuro-inspired computing chips,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:59.147006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4219cc06-2fcd-42be-853f-12c10459b203 · outbound

This paper cites 29.1 a 40nm 64kb 56.67tops/w read-disturb-tolerant compute-in-memory/digital rram macro with active-feedback-based read and in-situ write verification,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory 29.1 a 40nm 64kb 56.67tops/w read-disturb-tolerant compute-in-memory/digital rram macro with active-feedback-based read and in-situ write verification,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:58.977435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 392fa715-5f6b-478f-b3fc-979a7c6201ff · outbound

This paper cites A 40nm 64kb 26.56tops/w 2.37mb/mm2rram binary/compute-in-memory macro with 4.23x im- provement in density and 75% use of sensing dynamic range,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory A 40nm 64kb 26.56tops/w 2.37mb/mm2rram binary/compute-in-memory macro with 4.23x im- provement in density and 75% use of sensing dynamic range,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:58.800342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 28a03c82-2d43-4a52-b21f-a648b8720549 · outbound

This paper cites 34.4 a 3nm, 32.5tops/w, 55.0tops/mm2 and 3.78mb/mm2 fully-digital compute-in-memory macro supporting int12 × int12 with a parallel-mac architecture and foundry 6t-sram bit cell,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory 34.4 a 3nm, 32.5tops/w, 55.0tops/mm2 and 3.78mb/mm2 fully-digital compute-in-memory macro supporting int12 × int12 with a parallel-mac architecture and foundry 6t-sram bit cell,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:58.610949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0ea34bda-14b5-4dda-8a45-6e3c98d1b978 · outbound

This paper cites A 22nm 832kb hybrid-domain floating-point sram in-memory-compute macro with 16.2-70.2tflops/w for high-accuracy ai-edge devices,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory A 22nm 832kb hybrid-domain floating-point sram in-memory-compute macro with 16.2-70.2tflops/w for high-accuracy ai-edge devices,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:58.435469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6858b6ef-6480-4983-a8b1-d0d4146ad49c · outbound

This paper cites 34.2 a 16nm 96kb integer/floating- point dual-mode-gain-cell-computing-in-memory macro achieving 73.3- 163.3tops/w and 33.2-91.2tflops/w for ai-edge devices,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory 34.2 a 16nm 96kb integer/floating- point dual-mode-gain-cell-computing-in-memory macro achieving 73.3- 163.3tops/w and 33.2-91.2tflops/w for ai-edge devices,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:58.276951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f4db365a-0d0d-4177-a0aa-b806b26224b9 · outbound

This paper cites 34.8 a 22nm 16mb floating-point reram compute-in-memory macro with 31.2tflops/w for ai edge devices,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory 34.8 a 22nm 16mb floating-point reram compute-in-memory macro with 31.2tflops/w for ai edge devices,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:58.080794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a422149f-6347-4531-9e0c-013b3bc0d07b · outbound

This paper cites Efficient processing of mlperf mobile workloads using digital compute- in-memory macros,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Efficient processing of mlperf mobile workloads using digital compute- in-memory macros,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:57.752212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation defe39ca-bffb-4ed6-bc4e-4b40adf585cd · outbound

This paper cites 14.2 a 16nm 216kb, 188.4tops/w and 133.5tflops/w microscaling multi- mode gain-cell cim macro edge-ai devices,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory 14.2 a 16nm 216kb, 188.4tops/w and 133.5tflops/w microscaling multi- mode gain-cell cim macro edge-ai devices,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:57.605545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 477f43a0-1699-4b05-82ac-601191344b0d · outbound

This paper cites Addition is most you need: Efficient floating-point sram compute-in-memory by harnessing mantissa addition,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Addition is most you need: Efficient floating-point sram compute-in-memory by harnessing mantissa addition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:57.441618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 11c0f7c2-edfc-432e-9c2b-d079c4dc26ca · outbound

This paper cites Neural- pim: Efficient processing-in-memory with neural approximation of pe- ripherals,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Neural- pim: Efficient processing-in-memory with neural approximation of pe- ripherals,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:57.306377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 03cc2e92-9a8d-49bf-bad2-99970edff142 · outbound

This paper cites A hybrid-domain floating-point compute- in-memory architecture for efficient acceleration of high-precision deep neural networks,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory A hybrid-domain floating-point compute- in-memory architecture for efficient acceleration of high-precision deep neural networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:57.144004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 914ee612-fcec-4730-ae27-8af9984857ef · outbound

This paper cites A 5-nm 254-tops/w 221-tops/mm 2 fully-digital computing-in-memory macro supporting wide-range dynamic-voltage-frequency scaling and simultaneous mac and write operations,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory A 5-nm 254-tops/w 221-tops/mm 2 fully-digital computing-in-memory macro supporting wide-range dynamic-voltage-frequency scaling and simultaneous mac and write operations,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:57.003229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a3529df0-d12a-4a85-98d6-817ee8613315 · outbound

This paper cites Design possibilities and challenges of dnn models: a review on the perspective of end devices,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Design possibilities and challenges of dnn models: a review on the perspective of end devices,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:56.847479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 37b409c2-b92b-4863-b8ba-4e1be5267890 · outbound

This paper cites 13.8 a 32kb sram for error-free and error-tolerant applications with dynamic energy-quality management in 28nm cmos,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory 13.8 a 32kb sram for error-free and error-tolerant applications with dynamic energy-quality management in 28nm cmos,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:56.675008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38bccbb5-6934-4bf6-a702-545ef45c0cbb · outbound

This paper cites Etcim: An error-tolerant digital-cim processor with redundancy-free repair and run-time mac and cell error correction,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Etcim: An error-tolerant digital-cim processor with redundancy-free repair and run-time mac and cell error correction,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:56.526197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5d1668fd-3221-4887-9f9c-04c5766b6732 · outbound

This paper cites Cim-secded: A 40nm 64kb compute in-memory rram macro with ecc enabling reliable operation,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Cim-secded: A 40nm 64kb compute in-memory rram macro with ecc enabling reliable operation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:56.366146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4465f1ac-9aee-4701-b035-34d8ab699028 · outbound

This paper cites Improving compute in-memory ecc relia- bility with successive correction,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Improving compute in-memory ecc relia- bility with successive correction,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:31:53.978133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc3f6434-417d-4876-b891-714b445c27c8 · outbound

This paper cites Pytorchfi: A runtime perturbation tool for dnns,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Pytorchfi: A runtime perturbation tool for dnns,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:56.189352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a2e923ae-04a4-4f4a-b7ef-e32ee5f894cf · outbound

This paper cites Tensorfi: A flexible fault injection framework for tensor- flow applications,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Tensorfi: A flexible fault injection framework for tensor- flow applications,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:56.014513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 001423c7-664f-4357-8e9e-f8166238dc4c · outbound

This paper cites Ares: A framework for quantifying the resilience of deep neural networks,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Ares: A framework for quantifying the resilience of deep neural networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:55.834183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d42164e4-b8c8-48b8-b3c4-c67959b5cedd · outbound

This paper cites How accurately can soft error impact be estimated in black-box/white- box cases? – a case study with an edge ai soc –,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory How accurately can soft error impact be estimated in black-box/white- box cases? – a case study with an edge ai soc –,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:31:54.356365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 884b9157-eac6-47b2-81f2-857fdbd7971a · outbound

This paper cites Low-cost concurrent error detection for floating-point unit (fpu) controllers,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Low-cost concurrent error detection for floating-point unit (fpu) controllers,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:55.632202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8ff4aa38-9d83-4073-ae78-0715b2f84f82 · outbound

This paper cites When single event upset meets deep neural networks: Observations, explorations, and remedies,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory When single event upset meets deep neural networks: Observations, explorations, and remedies,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:55.479327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6ce3848e-7361-4af4-9741-978dd98ba302 · outbound

This paper cites Mac-ecc: In-situ error correction and its design methodology for reliable nvm-based compute-in-memory inference engine,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Mac-ecc: In-situ error correction and its design methodology for reliable nvm-based compute-in-memory inference engine,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:55.268724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 57e04533-ff83-4f46-a395-f9410dc5af00 · outbound

This paper cites What types of ecc should be used on flash memory,.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory What types of ecc should be used on flash memory,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:55.062721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 479ef63a-6e81-44f2-9f74-8a08dd6fa3d6 · outbound

This paper cites an unresolved cited work.

Unicorn-CIM: Uncovering the Vulnerability and Improving the Resilience of High-Precision Compute-in-Memory Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:31:57.908063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.