Pith. sign in

Paper Citation Record · LEDGER

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training

As of 8 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2602.21321.

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

pith.paper-citation-record.v1
2602.21321 v2

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T21:10:07.689537Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81043bc9-5e30-4c90-9d53-5cef14d2e9f0 · outbound

This paper cites In practice, however, the SP of an analog device is usually determined experimentally by applying alternating positive and negative update pulses until the weight converges.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training In practice, however, the SP of an analog device is usually determined experimentally by applying alternating positive and negative update pulses until the weight converges

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:07.689537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:07.689537Z digest=sha256:51c175862dcc9748f27882bb9bc5dfe036356fd300c5f9d8643e4b67b92cb483

Observation dd2f0d4c-48ea-4cac-b7c4-fd56aa1c497b · outbound

This paper cites Approximation Methods for Bilevel Programming.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training Approximation Methods for Bilevel Programming

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:05.869042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:05.869042Z digest=sha256:1827db243a7d33ef53d9be79dfef0bba88469f7c7ad4dca1c9afdc87c0abaebf

Observation 3e4c601c-1170-4bdc-b7a6-4b797ffe3104 · outbound

This paper cites Comparison of E-RIDER, Residual Learning/TT-v2 and AGAD The proposed E-RIDER has a similar form of AGAD (Rasch et al., 2023).

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training Comparison of E-RIDER, Residual Learning/TT-v2 and AGAD The proposed E-RIDER has a similar form of AGAD (Rasch et al., 2023)

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:07.346222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:07.346222Z digest=sha256:25e6380cef4890edcb992c8b65a71c92ce48d01ffe6abacf10139e26192d8770

Observation 7478a9ae-7182-416d-9fcf-5004c1135422 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training LLaMA: Open and Efficient Foundation Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:06.931715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:06.931715Z digest=sha256:d65224ae5e40d7f927f52bce1b8704ba46b5ea9eb0e914bed8a3103727ab300a

Observation 69821208-2ab0-4cdc-8895-5b8cfb323704 · outbound

This paper cites With a slight abuse of notation, we also define the pseudo-inverse of a vectorW∈R D asW † :=diag(W) †.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training With a slight abuse of notation, we also define the pseudo-inverse of a vectorW∈R D asW † :=diag(W) †

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:07.151013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:07.151013Z digest=sha256:a4016a6297d2fdbb4eeb2e0121594deeaeebb81db749dc537d826d9f3575e0a0

Observation 05e51751-ee3b-4b4c-a156-25324a03701c · outbound

This paper cites 18 Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training D.2.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training 18 Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training D.2

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:07.523151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:07.523151Z digest=sha256:6860fe937f7a9f24bbe60561bd169767c2db95f39eaf3afe0b5c4b317c2348b8

Observation e59678a9-dce6-4b11-852f-aa178369b9f9 · outbound

This paper cites Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:06.218573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:06.218573Z digest=sha256:280a3ef9e902161962bdac51679750d327ad9c4e639c8bf6eedc26b7c1080541

Observation 5c38126b-b05c-44a2-bee7-85479af1d8be · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:05.748423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:05.748423Z digest=sha256:9b0951747ca9f02ad8d0f213f2511f4021d16f90f8bea0b955ab16272aa46ab7

Observation 927853ec-af94-4597-9688-3673cd0171d9 · outbound

This paper cites In- memory training on analog devices with limited conduc- tance states via multi-tile residual learning.arXiv preprint arXiv:2510.02516,.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training In- memory training on analog devices with limited conduc- tance states via multi-tile residual learning.arXiv preprint arXiv:2510.02516,

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:06.408747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:06.408747Z digest=sha256:6f71f4fdc37677a316ee7c5ac2cf34b76b407882b2d3b78c57fe8e54a33f590f

Observation 172062aa-fa0a-46ed-860c-965a4f6fadb6 · outbound

This paper cites Fast offset corrected in-memory training.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training Fast offset corrected in-memory training

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:06.675272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:06.675272Z digest=sha256:ba5c147aa4a5b345d21763eedfcdfbddfd0ae17a07d0a26aa42079f3198e69cf

Observation c3209168-bc90-435f-b6c0-0f83d7593067 · outbound

This paper cites A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic.

Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-02T21:10:06.044687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:10:06.044687Z digest=sha256:c7d15002fcc951a4c6b4f40ad028597bbbdfc75607b73a6e0a4280392a24f006

Pith citing papers

No inbound Pith citation observations are available.