Pith. sign in

Paper Citation Record · LEDGER

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback

As of 19 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2412.17737.

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

pith.paper-citation-record.v1
2412.17737 v6

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:17:50.586922Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:52:14.182478Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T00:52:14.275313Z

Reference resolution

23 of 23 outbound references displayed

  • verified exact5
  • verified fuzzy8
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cf847e75-8dc5-4680-b84c-ae9afc9a71cb · outbound

This paper cites Zico Kolter.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Zico Kolter

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:51.082202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.469018Z digest=sha256:287624a0e8a6889e813c0b9a8b7bd13ea220a4a07b99d17eadd4f460915eb00c

Observation 39169499-2f7f-4721-99a2-d4f9289c5fdf · outbound

This paper cites Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-11T05:17:50.922192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.474869Z digest=sha256:4c28982ec8938866850caa8f9aac9494eabfdcb8cdedaf484073edc0029e5a38

Observation fd00c3ad-403d-4346-977f-50549c73e31e · outbound

This paper cites an unresolved cited work.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.480775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.480775Z digest=sha256:278e6b2654aae5f7486430c3322a688d29f0b24314580411f6d10c40c8eccb99

Observation b249fb2f-50e1-4fd7-a467-628dd29ff67c · outbound

This paper cites The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11 0 (2): 0 127--138, 2010.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11 0 (2): 0 127--138, 2010

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.486950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.486950Z digest=sha256:7a7d58a99ddf67bea8322d8a86d591a319de84cab2dc20e9feaf70a241f0b27c

Observation ac172cbc-d47b-4aec-958b-c0637ede7576 · outbound

This paper cites Draw: A recurrent neural network for image generation.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Draw: A recurrent neural network for image generation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:51.054212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.494669Z digest=sha256:f7ec73ca31ef0c7da20fa94c386a8c58af727bc542c646b190bb2a5e50dc26f6

Observation 5ccc380f-baeb-4e9f-815f-dc745ccf6e77 · outbound

This paper cites Towards solving the hard problem of consciousness: The varieties of brain resonances and the conscious experiences that they support.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Towards solving the hard problem of consciousness: The varieties of brain resonances and the conscious experiences that they support

Reference 6

Resolution
verified exact
doi, observed 2026-08-11T05:17:50.671664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.500416Z digest=sha256:a8baf8c88dfa71d8b2dc1ae6c47236857b7429bf4fb14b70b961db90a611408d

Observation 15d67a68-d4b5-4c27-b557-edc04ae7abeb · outbound

This paper cites Model-based Iterative Restoration for Binary Document Image Compression with Dictionary Learning.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Model-based Iterative Restoration for Binary Document Image Compression with Dictionary Learning

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T05:17:50.899079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.506362Z digest=sha256:dc2eb664cfeec6ed1b57b023b38bf6413ed2cd8d8a4a124d43c3554a55fae7fe

Observation 7b7d2847-3880-402c-94f2-c6119a023dea · outbound

This paper cites Hinton, Peter Dayan, Brendan J.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Hinton, Peter Dayan, Brendan J

Reference 8

Resolution
verified exact
doi, observed 2026-08-11T05:17:50.654581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.512059Z digest=sha256:2c944751e1cae0ec3cfae3064d71c7b1f0903a21725889b0c01007c8c8ce570a

Observation f418315e-2d34-4229-ad22-7ff1abc1f156 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback LoRA: Low-Rank Adaptation of Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.517521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.517521Z digest=sha256:139b2c4c589170826c13d6a68d720b3d37ce59c7f5ca3719e5c61596a2d8feb2

Observation 04846610-8a73-4df9-80a0-0a9a2c7f1486 · outbound

This paper cites Neural networks with recurrent generative feedback.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Neural networks with recurrent generative feedback

Reference 10

Resolution
verified exact
raw_fallback, observed 2026-08-11T05:17:50.858051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.522591Z digest=sha256:7e4fa715e68e4234f69288c4edceb469291d700b3413105350c62635d390d584

Observation 5ef82b48-ef29-43f7-87b1-e5f8ac24a962 · outbound

This paper cites an unresolved cited work.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:17:51.037445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.526797Z digest=sha256:2608addf6ec813213dc2cb8ece3d5911356e2f40c9bb7107801e2ada02f89518

Observation c2478205-9e5b-4bb0-9910-8a898c67fdb4 · outbound

This paper cites Deep learning.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Deep learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.530895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.530895Z digest=sha256:2c207891813700a3070e15cd693c7a437cd4b35150ca6dcba84b0d2676bd39fe

Observation 7ae02117-53d9-423d-8c8c-50654286ebce · outbound

This paper cites Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.535542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.535542Z digest=sha256:fa581f70488ddfac7be2cc19be029386c035c51277de61f02ac38a3dceca0763

Observation 4fc09cd2-bc9e-474e-8013-d37fd440c846 · outbound

This paper cites FiLM: Visual Reasoning with a General Conditioning Layer.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback FiLM: Visual Reasoning with a General Conditioning Layer

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.540373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.540373Z digest=sha256:ef6489ba32b2bbead4b300c6d4645a2a4d698e9e9e3dff5ddd175da62bbac9c0

Observation 21299bc8-e303-4a95-a2f8-00fa9378437d · outbound

This paper cites Compressive Transformers for Long-Range Sequence Modelling.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Compressive Transformers for Long-Range Sequence Modelling

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.546090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.546090Z digest=sha256:98dcedde907f3d2ef13c30d10dc744c04cdbe4a19a01277cee4e6c381e7f8e10

Observation 293c4a83-60e4-4582-9f5b-975161c4c080 · outbound

This paper cites Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:51.022187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.551740Z digest=sha256:75995a6b85716eebc11f8051503f1f349e571b84387ed288d930e565eb9194f8

Observation 9cd39966-744c-423d-96c6-e7ca7e144530 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback U-net: Convolutional networks for biomedical image segmentation

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:51.003947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.556578Z digest=sha256:73e733e180ba4db48ba887fc29976a7b3d720e08a82a24dfd4f17c0135d4ac61

Observation 975e9277-1ddf-49bc-924a-7619012b13ff · outbound

This paper cites Dynamic routing between capsules.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Dynamic routing between capsules

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:50.988447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.561486Z digest=sha256:5eafcabe92236ab95cb5435d22f68a45b9c29ec625275ea7a5224be3683e0f2c

Observation 256fc0ef-89d9-47cd-8e41-48b4e232720c · outbound

This paper cites Recurrent convolutional neural networks: A better model of biological object recognition.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Recurrent convolutional neural networks: A better model of biological object recognition

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:50.971647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.566374Z digest=sha256:319f63f289d59bc0403e6db350b15728c29c3f7103cbb39ea418e6857c396b7b

Observation 4cd55a65-0922-48b2-83b7-09b3781d5301 · outbound

This paper cites an unresolved cited work.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Unresolved cited work

Reference 20

Resolution
verified exact
doi, observed 2026-08-11T05:17:50.626221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.571219Z digest=sha256:16bd3eb3b3c04a3d8f1504258b22144bef99da9d4f46adfe62e193b9a4ecc1fc

Observation f49cc8da-5017-4c50-a1ab-5a332a32d54d · outbound

This paper cites Long Range Arena: A Benchmark for Efficient Transformers.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Long Range Arena: A Benchmark for Efficient Transformers

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T05:17:50.576602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:17:50.576602Z digest=sha256:f089fa7f80bb4b31091949774359c319dd61f98297b7c93a998710821127a526

Observation 9f5ae3a1-1949-4ee8-84ee-da1c8896cf6b · outbound

This paper cites Recurrent attentive zooming for joint crowd counting and precise localization.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Recurrent attentive zooming for joint crowd counting and precise localization

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:50.954729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.581985Z digest=sha256:25fc0494fe4329b5cba4d0746500d874946413a003ac2d796530b303ba1e4d33

Observation b19a2b90-04d8-438c-954b-630b33bdd6c6 · outbound

This paper cites Zamir, Te-Lin Wu, Lin Sun, William B.

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback Zamir, Te-Lin Wu, Lin Sun, William B

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:17:50.938686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:17:50.586922Z digest=sha256:0cc21c3c2ea0b66b3b409861abdf1f69302fc81f0a59e8a903c185272928ced0

Pith citing papers

Observation ddd7fc60-926a-4024-ae36-a7e25be86da6 · inbound

Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence cites this paper.

Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-09T00:52:14.280057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-09T00:52:14.182478Z digest=sha256:ed3a8273549794350a68c5fdf909284f2c98b4223ef004da467ed51068f2e42c