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Paper Citation Record · LEDGER

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

As of 20 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:1906.09624.

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

pith.paper-citation-record.v1
1906.09624 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T17:33:56.918863Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T14:35:55.709732Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:50:57.028932Z

Reference resolution

36 of 36 outbound references displayed

  • verified exact6
  • verified fuzzy25
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f9a6e9bf-9498-4f53-ac25-5f938ad5b4a3 · outbound

This paper cites write newline.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference write newline

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.789061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:b7da012a32670034b53c230210f51a404b6d41acfbab78ac52555dd1bb748b43

Observation 26e2a86f-0512-48c5-8098-12ac539c5ded · outbound

This paper cites and Ng, A.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Ng, A

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.793004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:642179a02610a4318181d7fa86676ca5f0bfdf71c65e2cbb0bd39441881bdb53

Observation 77b5de5f-6063-47de-a3d7-8c51bc312049 · outbound

This paper cites Learning from human preferences.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Learning from human preferences

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.785448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:dc15ea2672ef0e99554d63ddc7d42eb38b815266daa5334f77191b0a066b4a36

Observation 3c05d9c6-d592-418d-8463-a6316bf42b7a · outbound

This paper cites and Mindermann, S.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Mindermann, S

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.782048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:9421e8e48430dcfbdd3c3cdc7ef5a7ab08d02b4f26b6765aec255307755f185b

Observation 193bf705-5cf7-4b4b-94b0-bd5ed66ddeb5 · outbound

This paper cites an unresolved cited work.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-05-25T17:37:05.772292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:94f3b09fc80e78a8da0300aed16f34ef8011d877c0c944879a52a4074d9a1fa2

Observation e8f101c9-350d-4682-95a6-d59e15f2a6a0 · outbound

This paper cites an unresolved cited work.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-05-25T17:37:05.769274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:8ad7e0ebaf6421f3cf2b795f3408cae8de02135db88477b6d43c56dcb1f270f7

Observation 767671ce-bfbb-4b2e-a31e-8246bca7043f · outbound

This paper cites planning fallacy.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference planning fallacy

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.779163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:3e777955fe7c793dbb2b3254f451e7a035867b08dd9ebe21c73ab0af703caaad

Observation f6fbc452-286f-4db7-8fdf-c5ca48d683bc · outbound

This paper cites and Kim, K.-E.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Kim, K.-E

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.739648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:b3fa24ae49e997817765cb10156168b26d0a765ef1088cf30a6e172e164b97f8

Observation 1cbc551f-505a-4dc1-8ed9-abd5bfc600d7 · outbound

This paper cites The easy goal inference problem is still hard.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference The easy goal inference problem is still hard

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.752233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:9940e3280d23a189330a702f8e91a382df60cd259f949419b1641500b283b307

Observation 735b2c2e-e947-4ac1-a3c1-2e3ce8f481dc · outbound

This paper cites and Rothkopf, C.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Rothkopf, C

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.751712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:6fc13341de1a327abd4b2342abc6e605dd2ae706079e13eadda2d42e660f3171

Observation a5013674-fbe8-4304-b25d-19923ddaa0ad · outbound

This paper cites and Goodman, N.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Goodman, N

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.748118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:01a7444aba41f4b1c73ae74c60d6c927648bbb5089a29b2f45bb139d0e29b1c5

Observation 1af2b87f-67d2-43f9-a3f8-20d5c74df4cd · outbound

This paper cites an unresolved cited work.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-05-25T17:37:05.744590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:2ec395b80b9c8e6eb954690eb5d02bc2999cb97b267ce0f82019292379659003

Observation f514c3cb-791d-4a11-8073-adf486d44e67 · outbound

This paper cites Guided cost learning: Deep inverse optimal control via policy optimization.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Guided cost learning: Deep inverse optimal control via policy optimization

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.762312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:1a27361df7382e26bdd86ae66b9a60dd6ff9fbb8dad78ae1d02c2b7041ea3e1a

Observation d1604d1d-1c1d-4c7b-80d0-c23ebf32d61d · outbound

This paper cites Time discounting and time preference: A critical review.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Time discounting and time preference: A critical review

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.729197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:9b45f4243baf58b1b6ba0548a7a0d97ad0e238d7a4e08d252f2b97da6e2e9713

Observation e782b411-6eb1-48c9-8348-74b46bb0e138 · outbound

This paper cites Multi-task Maximum Entropy Inverse Reinforcement Learning.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Multi-task Maximum Entropy Inverse Reinforcement Learning

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-25T17:36:05.753031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:8189fddc6d00e30f189f966787eb858742080f7d7d5f9d908462a8a7a79a22ca

Observation 693ac56f-77bf-4623-802d-636ac2ea1880 · outbound

This paper cites Learning to Search with MCTSnets.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Learning to Search with MCTSnets

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-25T17:36:05.718801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:a2933901d4ea422f6b84f92674d02c647832035f5714f60ba72c5c70528489e6

Observation 3b4dbd0b-5ccd-4530-932f-e887ac9ad469 · outbound

This paper cites J., and Dragan, A.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference J., and Dragan, A

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.775715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:76befa9128ee7706f74718e62c3c936fee7075976448ee00c95ef78b90208c54

Observation 23bd822e-2431-4e82-9a7c-5b779ed17794 · outbound

This paper cites A perspective on judgment and choice: mapping bounded rationality.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference A perspective on judgment and choice: mapping bounded rationality

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.755806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:ea9269113cdbe65bd8dbd04781088b7554daeecf74afcfd59ba075c78b8201e5

Observation b887dcf2-7868-4167-bb9c-d3d702316007 · outbound

This paper cites Specification gaming examples in ai.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Specification gaming examples in ai

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.763279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:c64e8e1e4878b9a77031914fde2aa55752e4837e13b33eb215ace4db8cb803b4

Observation be275a38-9860-4fad-8a6e-eeb5ec6ff86c · outbound

This paper cites Risk-sensitive inverse reinforcement learning via coherent risk models.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Risk-sensitive inverse reinforcement learning via coherent risk models

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.759451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:88f974cf2d5ad31b507988aba56422dc54dae4761d661d9c5f70b865006c6cdb

Observation 56950a82-5761-4c44-a5aa-65a238e37afd · outbound

This paper cites Y., Russell, S.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Y., Russell, S

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.741393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:82428d55caec087788ab8ea139daf8ee22a2361609ac7f134fc92addb80585b4

Observation b9913298-4bcc-41a7-84c7-14f154df20e8 · outbound

This paper cites Feature visualization.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Feature visualization

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.795748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:9d66da78fed4e71d0e35ff4e39c44443f3a6c4a035c846ec8b953a5535576dde

Observation 61ab85df-20b3-4953-a8d2-da32723ea0e3 · outbound

This paper cites Learning model-based planning from scratch.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Learning model-based planning from scratch

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-05-25T17:36:05.725294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:4ee49f83b962ee94eb80c39b6fbd60cd88acc315cdcffdfdeff54ea546254f2d

Observation 667b0124-3235-4e53-8c45-e53c9379e5a2 · outbound

This paper cites an unresolved cited work.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-05-25T17:37:05.784669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:76c8a7855a895f2a4488a67c19b32701933f6aeacf38fce41c15c6b3968efe83

Observation eab746cc-61e7-4515-ac5f-983210fa1049 · outbound

This paper cites Machine Theory of Mind.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Machine Theory of Mind

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-05-25T17:36:05.732608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:9e74eb47431355dbdbb86890eaadc9393f1b17b6790f6e5a83ee37559cca7bf1

Observation 6c41499b-dd99-4e74-924a-d000df67156f · outbound

This paper cites Where do you think you're going?: Inferring beliefs about dynamics from behavior.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Where do you think you're going?: Inferring beliefs about dynamics from behavior

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.788935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:fab9a07cfdf4c37077c2f19f56c7cf6caaf59bd0e91331f6ae88c145d18cd893

Observation 3646b5bd-076a-41c9-b119-87b7eb57b9ce · outbound

This paper cites Learning agents for uncertain environments.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Learning agents for uncertain environments

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.702366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:22d4c5a707b9b71abc828fddd179dce2be4bb946921f35eb49f76a53425143f0

Observation 92b912de-f170-4396-939e-e930cb1c4b8a · outbound

This paper cites Inverse reinforcement learning from failure.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Inverse reinforcement learning from failure

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.777621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:d17a48e6b4f42e114a1ae6c659f7e0b932a5c73b09f26934141ae5ebde2e453b

Observation f9cdf10e-d340-41ea-8a20-a6999f8d3d82 · outbound

This paper cites Universal Planning Networks.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Universal Planning Networks

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-05-25T17:36:05.739165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:cd9a838c4f34ef4f60b2e2f8dd63acb237a352f76cc757c446d2ff173d7be584

Observation 1af7be0c-c56d-45ce-b586-0bdd95715b6b · outbound

This paper cites Latent variables and model mis-specification.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Latent variables and model mis-specification

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.781207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:319097db6a68d10809d40c01bfe33d5c49e4a5679785152bec890140ac44ada3

Observation 3efd5067-b471-40a5-b3da-e36d7c46f49d · outbound

This paper cites and Evans, O.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Evans, O

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.792285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:1736b5dcf1c7a502d9d232d404628f668276b92a4a9e50ee641df18d3a2ce360

Observation 0f0ce870-7300-4a21-a28a-4061421fa776 · outbound

This paper cites Value iteration networks.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Value iteration networks

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.799617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:f3cc229330db57d7d7128d8333cff05ca295455a105aa6ad255d6037baf8e74c

Observation 1f648b7b-962e-4888-ae17-5b08e458f425 · outbound

This paper cites and Kahneman, D.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference and Kahneman, D

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-25T17:37:05.773711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:aa9dd8ba5705974971140c288d1aa1e804b41f3b757e53c623d46551011488b2

Observation b36a48f2-a461-4f32-9728-0737055dbcde · outbound

This paper cites Learning a Prior over Intent via Meta-Inverse Reinforcement Learning.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Learning a Prior over Intent via Meta-Inverse Reinforcement Learning

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-25T17:36:05.746471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-25T17:33:56.918863Z digest=sha256:8ce8994e3c67cdcfa335a002db33c1e0e0a70105a92f88b4f73c0896d5eef7c4

Observation a4a2fe69-97b4-4d29-b5f0-32e14b136c93 · outbound

This paper cites an unresolved cited work.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-05-25T17:37:05.766595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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This paper cites D., Maas, A.

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference D., Maas, A

Reference 36

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Pith citing papers

Observation c999d903-9ad4-4a83-8059-3382c556d2bf · inbound

Mitigating Cognitive Bias in RLHF by Altering Rationality cites this paper.

Mitigating Cognitive Bias in RLHF by Altering Rationality On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

Reference 16

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arxiv_id, observed 2026-07-04T23:44:00.157209Z

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Observation e084806b-b6e8-4988-bfbb-7f96090ddea7 · inbound

Constructive Alignment: Governing Preference Dynamics in Human-AI Interaction cites this paper.

Constructive Alignment: Governing Preference Dynamics in Human-AI Interaction On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

Reference 141

Resolution
unresolved
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Unavailable: canonical work link unavailable.

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