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Paper Citation Record · LEDGER

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models

As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 3 inbound Pith citation observations for arXiv:2602.13215.

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

pith.paper-citation-record.v1
2602.13215 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T11:48:50.587732Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:48:49.999005Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact14
  • verified fuzzy1
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5554fabb-e80d-4a4a-866a-e994eee42072 · outbound

This paper cites PonderNet: Learning to Ponder.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models PonderNet: Learning to Ponder

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-16T11:50:52.806057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:82f83136b567a9f72669ad29c4b34e09d5350b270549dc5cf1add61b808b2722

Observation 48b832bd-07b3-4b4b-a3ea-702c784d7722 · outbound

This paper cites Longformer: The Long-Document Transformer.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Longformer: The Long-Document Transformer

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.799553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:3f408b8f1053da9a8b75bde864d0507f8f7d3b42758e5571ec51dd18ceabc82d

Observation fc704906-14c5-43a3-9175-00e084293445 · outbound

This paper cites The Consciousness Prior.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models The Consciousness Prior

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T11:50:52.809099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:ec625f5c64197445fbc1c295b836672246240f5fec7108052038bf171f6f5c4c

Observation c8897181-6760-4a82-a168-997cfdb18d24 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.814781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:909680efad4d6b17893e1ca1673521e5d1b758882337ee11e0f9a250fe1a0de8

Observation 7f6c6f70-552f-4f1d-9ead-0eb9edd9c3bb · outbound

This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.811809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:eb672c69ee50c417378578d7e30a2e0b151b6de2db56e59c32f1f89112d8d7b9

Observation 18a0e62c-33ee-474a-9528-d0cb10165e65 · outbound

This paper cites Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 6

Resolution
metadata mismatch
local_arxiv, observed 2026-05-16T11:50:52.802578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:9d0bbf001cb11d7a12583e2b9a1e44e3c54cded86a6b6408bc7082ff46de9799

Observation a624811f-df97-43d8-a275-32d8201fa572 · outbound

This paper cites Hymba: A Hybrid-head Architecture for Small Language Models.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Hymba: A Hybrid-head Architecture for Small Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-16T11:50:52.833832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:f9090d22c26d7190f2959f17c1d8e18cf00a7d7f3bad501af42fdcddb215a2e3

Observation 8a339f8f-562c-4d51-afc2-97b15f311a07 · outbound

This paper cites Zamba: A Compact 7B SSM Hybrid Model.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Zamba: A Compact 7B SSM Hybrid Model

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-16T11:50:52.818598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:76e955c876a19ba3388688c0898d652d9a933ee06b61f9bcc807f0e3efc68b78

Observation 2f42d2cc-398b-4e91-b7f1-ea7926035346 · outbound

This paper cites Adaptive Computation Time for Recurrent Neural Networks.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Adaptive Computation Time for Recurrent Neural Networks

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.827980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:d7e1afc8da230ac87276f5446e37e2a18f8fe32008719848dbf30c8af6af1cbd

Observation 4125ba9d-78a7-4fd5-80d5-c11a97db5108 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.836641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:d06b6dda3751fdbe6cfd01e2008e3ecd0d27b528a3fbe98c8a5613c137824855

Observation 99d5147a-0249-44a1-92a5-6664dee0b31d · outbound

This paper cites Jamba: A Hybrid Transformer-Mamba Language Model.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Jamba: A Hybrid Transformer-Mamba Language Model

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.844574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:0d3e21962acb403d4ac50a65f6ef9c5c35bc7267dc9f0806a35b954ff3f29590

Observation dc0d1f82-4f9c-4c76-8a0a-76b837c8591a · outbound

This paper cites Rwkv: Reinventing rnns for the transformer era.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Rwkv: Reinventing rnns for the transformer era

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T11:50:53.162359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:46a2b480e4a17c17fef4428967ae9cb4a91f5465d27596db58a366caf8359c53

Observation 0022ec82-7cbd-4322-9d47-b445370b4794 · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:18:02.305925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:14106da77b8caf7cc52e08e43b2e5c7d70310c690f2fe28a0831bbffcdb2f29d

Observation 41dbce35-a554-4b68-9244-b6285de5609a · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Retentive Network: A Successor to Transformer for Large Language Models

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.841885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:f99e9944771500b0938153b5244d6e4244081c27f9d40fe77429e8befbf2337d

Observation 7d0313a8-11b6-471f-93c3-079cf5b58c9f · outbound

This paper cites Hierarchical Reasoning Model.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Hierarchical Reasoning Model

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.831212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:f28683843c3dbd24ff1bce72a55671fd5c115b97af1ca96e9cb8652ed119550a

Observation 8eb1fff1-0e02-45ae-ac9a-20c4fdf460ac · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Linformer: Self-Attention with Linear Complexity

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:50:52.839281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:4f98a660b02b04b4cad77327f4f1ee8c4e410ce1979c2785b653e2bb9fb31c28

Observation 839e6d1e-7e4e-4253-a082-ba6862a6619f · outbound

This paper cites Context-selective state space models: Feedback is all you need.arXiv preprint arXiv:2510.14027.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Context-selective state space models: Feedback is all you need.arXiv preprint arXiv:2510.14027

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-16T11:50:52.825278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T11:48:50.587732Z digest=sha256:c81aaba2d1cad455004bb9bea969af9a655ae205fae051f435c46dfb380d9916

Pith citing papers

Observation 15bf85ef-1f1f-4a30-9fee-f9fd7f5b5cfa · inbound

Memory for Large Language Models cites this paper.

Memory for Large Language Models When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-01T02:37:54.307962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T02:37:54.307962Z digest=sha256:535435b115ee42ad6e68252b943ed46a64687efb2458d33f01d2744831fbc627

Observation a74dd468-523f-4682-9436-e3b1e5c2c112 · inbound

From Found to Designed: Concepts as a Design Axis for Large Language Models cites this paper.

From Found to Designed: Concepts as a Design Axis for Large Language Models When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-30T19:59:22.911024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T19:59:22.911024Z digest=sha256:c1c45a5a22e08a982dc495836428c3f3a840eda2dd62b9d64f805a25aa91779f

Observation 5f9d8106-9558-472d-9ae2-bbc2249e2343 · inbound

From Found to Designed: Concepts as a Design Axis for Large Language Models cites this paper.

From Found to Designed: Concepts as a Design Axis for Large Language Models When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-01T10:48:49.999005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T10:48:49.999005Z digest=sha256:f45cc171f3ec0bab8158438a700216767bd01091a7c3dbba2415f345daebdf2f