Pith. sign in

Paper Citation Record · LEDGER

What Does it Mean for a Neural Network to Learn a "World Model"?

As of 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2507.21513.

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

pith.paper-citation-record.v1
2507.21513 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:44:47.061248Z

measured 26 of 26 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

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy6
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6286c621-91ba-48e8-9524-86b0e553b85f · outbound

This paper cites Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color.

What Does it Mean for a Neural Network to Learn a "World Model"? Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:44.684595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:44.684595Z digest=sha256:d19392c468955d63d31625f124e2dbcd98a3e3c7d2c04bd5e60afb6a3abf9c6f

Observation 3d48ef1e-f33e-48df-a4c5-5b1a930c8b5a · outbound

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

What Does it Mean for a Neural Network to Learn a "World Model"? Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.105857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.105857Z digest=sha256:1bc8adfb94cd0b29ba8dab58f650a0a069cb92938e8846066517d80d9fa35cd5

Observation ea1cd338-5a37-4259-84c5-763c53e6a279 · outbound

This paper cites World Models.

What Does it Mean for a Neural Network to Learn a "World Model"? World Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.239376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.239376Z digest=sha256:309a0ac491f571ad93b8919e53c8e26ab3b029b2a66f4b9a2e28d8924a65cb7e

Observation 591e9dd7-ea97-4d11-bdf5-183f5444bd15 · outbound

This paper cites Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task.

What Does it Mean for a Neural Network to Learn a "World Model"? Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.677714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.677714Z digest=sha256:8182ece56e8eaf447fcfb6f758963476bf41cd62db458aded4a3959e07c50de2

Observation b8f51a83-0023-4c75-841b-ae3c95aa4e1c · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

What Does it Mean for a Neural Network to Learn a "World Model"? Playing Atari with Deep Reinforcement Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.762383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.762383Z digest=sha256:cbb56e258d359619f71d6ab30add01ad42b0924cdad77155d228b9ba9850e458

Observation 9b485c08-7d18-450f-960c-c0e1db243b34 · outbound

This paper cites Glove: Global vectors for word representation.

What Does it Mean for a Neural Network to Learn a "World Model"? Glove: Global vectors for word representation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:44:48.418156Z

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.

source=pdf_text observed=2026-08-06T12:44:45.985105Z digest=sha256:a403468fee5d1b7eadbc06cd01bc7a6850da5a39aa5f5f5f639a981bc4f092c4

Observation 1b4c3c66-d130-468f-9ffd-784c53fd68b7 · outbound

This paper cites Are Emergent Abilities of Large Language Models a Mirage?.

What Does it Mean for a Neural Network to Learn a "World Model"? Are Emergent Abilities of Large Language Models a Mirage?

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.168916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.168916Z digest=sha256:de63ce88ac09960708d447f953fa823cfc63f486dcbe18b3eb23fbf78d9346b0

Observation 7fad64e8-305a-4376-9fbb-416512a7d58d · outbound

This paper cites Proximal Policy Optimization Algorithms.

What Does it Mean for a Neural Network to Learn a "World Model"? Proximal Policy Optimization Algorithms

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.243710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.243710Z digest=sha256:01e3451d0a7c9270d446d8df47db836a3100d4864ac37967f2e535c8843d6b0a

Observation d31759d9-4456-4e96-82a5-6807f12a6c34 · outbound

This paper cites Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

What Does it Mean for a Neural Network to Learn a "World Model"? Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.361511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.361511Z digest=sha256:982cf6139cc016241a0e0bf6adff6f3daf5de09718b4bb74ad4fcb4f07424691

Observation c145a485-1b06-43fb-aff9-c7ce4f3ad391 · outbound

This paper cites Detecting strange attractors in turbulence.

What Does it Mean for a Neural Network to Learn a "World Model"? Detecting strange attractors in turbulence

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:44:48.272685Z

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.

source=pdf_text observed=2026-08-06T12:44:46.443925Z digest=sha256:493a954b5c998a913e8a94e2a7bc7b29d3d88644b1c8e5abfa3d2d7a5437fe5f

Observation dc4f3591-904d-4298-9185-4194c1b1f435 · outbound

This paper cites Evaluating the World Model Implicit in a Generative Model.

What Does it Mean for a Neural Network to Learn a "World Model"? Evaluating the World Model Implicit in a Generative Model

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.541283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.541283Z digest=sha256:45d20981b53d0284230340426fe0b8e04cf90b84f1259eaa1ef831e4ce30cf1a

Observation 079575da-6efd-4e19-9194-e20e2339800d · outbound

This paper cites The System Model and the User Model: Exploring AI Dashboard Design.

What Does it Mean for a Neural Network to Learn a "World Model"? The System Model and the User Model: Exploring AI Dashboard Design

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.618587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.618587Z digest=sha256:de19633b86f9c6ff1655a3971c04fa85b72c3a87fba5a4448bd4af5fbf0c7926

Observation 7bcd501f-4f91-44bc-a337-3b28d596c3eb · outbound

This paper cites Emergence of Maps in the Memories of Blind Navigation Agents.

What Does it Mean for a Neural Network to Learn a "World Model"? Emergence of Maps in the Memories of Blind Navigation Agents

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.734328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.734328Z digest=sha256:de72738f8e594695a35d939606e0e1c7c10ef259879473ed824c0528cdbd4f48

Observation 9093a2ac-a8d0-4bbb-9e40-e099a9ffd600 · outbound

This paper cites From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought.

What Does it Mean for a Neural Network to Learn a "World Model"? From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.859237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.859237Z digest=sha256:e27330c9614e8337c7da1ace53fa8f3ca8afd55d0b2113eca559eaf14f8f4a9a

Observation a364708b-a200-457d-9ef1-484f899cc15c · outbound

This paper cites Making Large Language Models into World Models with Precondition and Effect Knowledge.

What Does it Mean for a Neural Network to Learn a "World Model"? Making Large Language Models into World Models with Precondition and Effect Knowledge

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.955953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.955953Z digest=sha256:d81050a8950cd8f6e1537c621030c69889fd879a8931489b7dcae9b405543730

Observation 919bb990-6d79-40dc-98d8-b61e08409386 · outbound

This paper cites good approximation.

What Does it Mean for a Neural Network to Learn a "World Model"? good approximation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:44:48.149316Z

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.

source=pdf_text observed=2026-08-06T12:44:47.061248Z digest=sha256:022ef7429612dfe53f19e4ee339921543a0a7e26daa3eb86bafbd0f88ab91bbf

Observation f775e219-37da-4fe5-b8ed-0c646af56bd1 · outbound

This paper cites On interpretability and feature representations: an analysis of the sentiment neuron.

What Does it Mean for a Neural Network to Learn a "World Model"? On interpretability and feature representations: an analysis of the sentiment neuron

Reference 1967

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:44:48.740157Z

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.

source=pdf_text observed=2026-08-06T12:44:45.026404Z digest=sha256:cb2e13c591cf49b5ae3186b141686c75712245257db34bb63e6fc8465e283c56

Observation c8bbf852-0562-422a-b615-80d0610d12ca · outbound

This paper cites Designing and Interpreting Probes with Control Tasks.

What Does it Mean for a Neural Network to Learn a "World Model"? Designing and Interpreting Probes with Control Tasks

Reference 2005

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.327246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.327246Z digest=sha256:286165d7e69b2222b632b151e67d3ee5a849ba92a5b3cecb610ea5c768db0018

Observation c51f6065-9d97-4a80-aaf5-ff084e78088c · outbound

This paper cites Progress measures for grokking via mechanistic interpretability.

What Does it Mean for a Neural Network to Learn a "World Model"? Progress measures for grokking via mechanistic interpretability

Reference 2013

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.857588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.857588Z digest=sha256:4ae69c90f50f15868394b842185ce07ed6d1f5bbc41ce3b2732c3a50d553ef3b

Observation 69a5b349-dab4-42c0-b721-548d6573281a · outbound

This paper cites Learning to Generate Reviews and Discovering Sentiment.

What Does it Mean for a Neural Network to Learn a "World Model"? Learning to Generate Reviews and Discovering Sentiment

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.073052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.073052Z digest=sha256:460a0d82b8afca198060d24d8abf1c637c5a44aa8e6aaec08d959c14fa7a97b8

Observation 8b15a018-5b2f-41d8-bd96-1d3fd6c4e905 · outbound

This paper cites Language Models as Agent Models.

What Does it Mean for a Neural Network to Learn a "World Model"? Language Models as Agent Models

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:44.861954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:44.861954Z digest=sha256:7d42a4e2a801d2dfeff4bf1f3e85d669ab101cf1cfe9ac753df266394fb758b4

Observation 251cec7b-5488-4721-82b9-d31c526dccc8 · outbound

This paper cites A path towards autonomous machine intelligence version 0.9.

What Does it Mean for a Neural Network to Learn a "World Model"? A path towards autonomous machine intelligence version 0.9

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:44:48.570737Z

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.

source=pdf_text observed=2026-08-06T12:44:45.426470Z digest=sha256:04666469ab0f1780348420a9aa6e6be4c24c9d63dfba81995816d67c3d5c9ecb

Observation e199c974-158e-41a5-91be-648f04a3b655 · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pp.

What Does it Mean for a Neural Network to Learn a "World Model"? On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pp

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:44:48.937734Z

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.

source=pdf_text observed=2026-08-06T12:44:44.946325Z digest=sha256:09bd386d1f9aebfcf220afd5e84c32827c58f7b0e9c8849296bee5d196a54ac7

Observation 869c6913-c7a2-4334-bdd0-7d95e39d5e19 · outbound

This paper cites Understanding intermediate layers using linear classifier probes.

What Does it Mean for a Neural Network to Learn a "World Model"? Understanding intermediate layers using linear classifier probes

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:44.766290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:44.766290Z digest=sha256:cfc8278f63e0a579dd1b4232a64c891101e29ff1075e205321dde3527541fb03

Observation c018aa5b-4895-44e6-bedf-238111973a5a · outbound

This paper cites Language Models Represent Space and Time.

What Does it Mean for a Neural Network to Learn a "World Model"? Language Models Represent Space and Time

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:45.163874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:45.163874Z digest=sha256:f1b5e8bf8bfa2a148cf0a0f108a74b5b4dc6351d58265d8b076b079a928ffcfc

Observation 84e9f17c-59e1-4c68-b09a-e57589f6e9f8 · outbound

This paper cites Belinda Z Li, Maxwell Nye, and Jacob Andreas.

What Does it Mean for a Neural Network to Learn a "World Model"? Belinda Z Li, Maxwell Nye, and Jacob Andreas

Reference 2024

Resolution
verified exact
raw_fallback, observed 2026-08-06T12:44:47.749505Z

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.

source=pdf_text observed=2026-08-06T12:44:45.600333Z digest=sha256:6a065dbed250fae598fd3caf3360c346d333f24368de5759e7cc021b19a69c5a

Pith citing papers

No inbound Pith citation observations are available.