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Paper Citation Record · LEDGER

Data augmentation as a framework for modeling hippocampal contributions to generalization

As of 17 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2608.01297.

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

pith.paper-citation-record.v1
2608.01297 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:25:22.239098Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

59 of 59 outbound references displayed

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Outbound references

Observation 1ed40343-0353-49c3-9bb4-879db582bad4 · outbound

This paper cites A cortical–hippocampal system for declarative memory.Nature Reviews Neuroscience, 1(1):41–50, 2000.

Data augmentation as a framework for modeling hippocampal contributions to generalization A cortical–hippocampal system for declarative memory.Nature Reviews Neuroscience, 1(1):41–50, 2000

Reference 1

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source=pdf_text observed=2026-08-06T00:25:18.191524Z digest=sha256:88d9269209537878b7cf8c13e3a42629e151fbac41b2a443b4bdba02f14b4477

Observation 59c76d66-856a-42a9-b0b1-69d8d0fc031a · outbound

This paper cites Medial temporal lobe amnesia: Gradual acquisition of factual information by nondeclarative memory.Journal of Neuroscience, 22(13):5741–5748, 2002.

Data augmentation as a framework for modeling hippocampal contributions to generalization Medial temporal lobe amnesia: Gradual acquisition of factual information by nondeclarative memory.Journal of Neuroscience, 22(13):5741–5748, 2002

Reference 2

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Observation b16c5458-5691-4a46-9870-d1bc0830eda0 · outbound

This paper cites Hippocampal replay is not a simple function of experience.Neuron, 65(5):695–705, 2010.

Data augmentation as a framework for modeling hippocampal contributions to generalization Hippocampal replay is not a simple function of experience.Neuron, 65(5):695–705, 2010

Reference 3

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Observation 10e45b27-8547-4daf-9a38-ee3464c37b6d · outbound

This paper cites Hippocampal place cells construct reward related sequences through unexplored space.Elife, 4:e06063, 2015.

Data augmentation as a framework for modeling hippocampal contributions to generalization Hippocampal place cells construct reward related sequences through unexplored space.Elife, 4:e06063, 2015

Reference 4

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source=pdf_text observed=2026-08-06T00:25:18.459373Z digest=sha256:dcabb093a8e5438d39d9d9cf2985dae58f23aed09ef99f6d1a1b08d024aa52dd

Observation 7e05eb86-d848-4700-9d20-30e33675b6e3 · outbound

This paper cites The hippocampus as a spatial map: Preliminary evidence from unit activity in the freely-moving rat.Brain Research, 34(1):171–175, 1971.

Data augmentation as a framework for modeling hippocampal contributions to generalization The hippocampus as a spatial map: Preliminary evidence from unit activity in the freely-moving rat.Brain Research, 34(1):171–175, 1971

Reference 5

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source=pdf_text observed=2026-08-06T00:25:18.537288Z digest=sha256:ba96fc0c7bcf6e9c2c51abfe4e283900149d3bc2ef52e313ccec23e1a566c9bd

Observation 6c4bb9ec-5120-434f-b43a-8d8fa9510c3d · outbound

This paper cites Time cells in the hippocampus: a new dimension for mapping memories.

Data augmentation as a framework for modeling hippocampal contributions to generalization Time cells in the hippocampus: a new dimension for mapping memories

Reference 6

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source=pdf_text observed=2026-08-06T00:25:18.603901Z digest=sha256:7ed9783ff0dc8538523704fd9ab3c8f9b6e22f532db3f703d859c44ccdbffc87

Observation 561d3a64-1aa8-4c24-bd3b-c33cf2db368d · outbound

This paper cites Cognitive maps in rats and men.Psychological Review, 55(4):189–208, 1948.

Data augmentation as a framework for modeling hippocampal contributions to generalization Cognitive maps in rats and men.Psychological Review, 55(4):189–208, 1948

Reference 7

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source=pdf_text observed=2026-08-06T00:25:18.652276Z digest=sha256:97c95493aa65bf8ca7c5a42f98c65194b406c85ad8a3cccde1cee8a5742c0875

Observation 214347ad-feeb-451b-92d2-ee08d314c18b · outbound

This paper cites Oxford University Press, 1978.

Data augmentation as a framework for modeling hippocampal contributions to generalization Oxford University Press, 1978

Reference 8

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source=pdf_text observed=2026-08-06T00:25:18.718150Z digest=sha256:d8fe9bc67a43ea043ee8d3cc97303320c87732cda9d661f5b6792d01148ae27c

Observation cdceec39-ba1a-4ac6-9c76-8ec2f7cb15e5 · outbound

This paper cites Simple memory: a theory for archicortex.Philosophical Transactions of the Royal Society of London B, 262(841):23–81, 1971.

Data augmentation as a framework for modeling hippocampal contributions to generalization Simple memory: a theory for archicortex.Philosophical Transactions of the Royal Society of London B, 262(841):23–81, 1971

Reference 9

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source=pdf_text observed=2026-08-06T00:25:18.779384Z digest=sha256:df4dbe8cf2e2a7bff64af91b31c3e9f44693cada40bd91a45748d59ad55c9c4c

Observation b60507df-4db7-449d-9d3b-18d1f1051f8f · outbound

This paper cites Computational analysis of the role of the hippocampus in memory.Hippocampus, 4(3):374–391, 1994.

Data augmentation as a framework for modeling hippocampal contributions to generalization Computational analysis of the role of the hippocampus in memory.Hippocampus, 4(3):374–391, 1994

Reference 10

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Observation d28c9a9e-d916-4152-a998-4df57b47e970 · outbound

This paper cites an unresolved cited work.

Data augmentation as a framework for modeling hippocampal contributions to generalization Unresolved cited work

Reference 11

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Observation 1f9ff67b-38e0-4cb3-b817-c1114ce38308 · outbound

This paper cites The hippocampus as a predictive map.Nature neuroscience, 20(11):1643–1653, 2017.

Data augmentation as a framework for modeling hippocampal contributions to generalization The hippocampus as a predictive map.Nature neuroscience, 20(11):1643–1653, 2017

Reference 12

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Observation babd1038-940b-4886-a957-0637fe16ea37 · outbound

This paper cites The successor representation in human reinforcement learning.

Data augmentation as a framework for modeling hippocampal contributions to generalization The successor representation in human reinforcement learning

Reference 13

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Observation 7699beb3-60c0-496a-9154-fa3de92a25ab · outbound

This paper cites The brain hierarchically rep- resents the past and future during multistep anticipation.Nature Communications, 15(1):9094, 2024.

Data augmentation as a framework for modeling hippocampal contributions to generalization The brain hierarchically rep- resents the past and future during multistep anticipation.Nature Communications, 15(1):9094, 2024

Reference 14

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Observation 23d5c4d5-f868-41af-8bd0-f3ac7fb21e70 · outbound

This paper cites The hippocampus and inferential reasoning: Building memories to navigate future decisions.Frontiers in Human Neuroscience, 6:70, 2012.

Data augmentation as a framework for modeling hippocampal contributions to generalization The hippocampus and inferential reasoning: Building memories to navigate future decisions.Frontiers in Human Neuroscience, 6:70, 2012

Reference 15

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Observation 32a7760e-edb2-4d5c-985f-4ea00c94b5ec · outbound

This paper cites The tolman-eichenbaum machine: unifying space and relational memory through generalization in the hippocampal formation.Cell, 183(5):1249– 1263, 2020.

Data augmentation as a framework for modeling hippocampal contributions to generalization The tolman-eichenbaum machine: unifying space and relational memory through generalization in the hippocampal formation.Cell, 183(5):1249– 1263, 2020

Reference 16

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Observation 4a056ffa-e482-49b4-81e4-195390ba3276 · outbound

This paper cites What is a cognitive map? organizing knowledge for flexible behavior.Neuron, 100(2):490–509, 2018.

Data augmentation as a framework for modeling hippocampal contributions to generalization What is a cognitive map? organizing knowledge for flexible behavior.Neuron, 100(2):490–509, 2018

Reference 17

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Observation a03ed684-1143-4493-8e6f-34a7aeb7fcf4 · outbound

This paper cites Semantic search as pattern completion across a concept.

Data augmentation as a framework for modeling hippocampal contributions to generalization Semantic search as pattern completion across a concept

Reference 18

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Observation 24c19007-937d-40ea-9864-6d83eeae17e9 · outbound

This paper cites A survey on image data augmentation for deep learning.Journal of Big Data, 6(1):1–48, 2019.

Data augmentation as a framework for modeling hippocampal contributions to generalization A survey on image data augmentation for deep learning.Journal of Big Data, 6(1):1–48, 2019

Reference 19

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Observation 4b062821-5ae4-4d7f-bf56-3e69c065f0dd · outbound

This paper cites Generalization through the recurrent interaction of episodic memories: a model of the hippocampal system.Psychological review, 119(3):573, 2012.

Data augmentation as a framework for modeling hippocampal contributions to generalization Generalization through the recurrent interaction of episodic memories: a model of the hippocampal system.Psychological review, 119(3):573, 2012

Reference 20

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Observation 01e63011-9b7c-47b0-bdef-f0c60764b18c · outbound

This paper cites A unifying account of replay as context-driven memory reactivation.eLife, 13:RP99931, 2026.

Data augmentation as a framework for modeling hippocampal contributions to generalization A unifying account of replay as context-driven memory reactivation.eLife, 13:RP99931, 2026

Reference 21

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Observation 830cd9e3-163e-455b-8c8a-4a9dd54a2956 · outbound

This paper cites Adaptive compression as a unifying framework for episodic and semantic memory.Nature Reviews Psychology, pages 1–15, 2025.

Data augmentation as a framework for modeling hippocampal contributions to generalization Adaptive compression as a unifying framework for episodic and semantic memory.Nature Reviews Psychology, pages 1–15, 2025

Reference 22

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Observation 22f79442-95ff-4c97-8e89-0bbf9277ca81 · outbound

This paper cites Dinov2: Learning robust visual features without supervision.Transactions on Machine Learning Research, 2024.

Data augmentation as a framework for modeling hippocampal contributions to generalization Dinov2: Learning robust visual features without supervision.Transactions on Machine Learning Research, 2024

Reference 23

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Observation b294b756-c023-4795-9ab0-ab555c683738 · outbound

This paper cites VGGT: Visual geometry grounded transformer.

Data augmentation as a framework for modeling hippocampal contributions to generalization VGGT: Visual geometry grounded transformer

Reference 24

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Observation 12435447-2ed3-401a-b95c-3176425ec2b9 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Data augmentation as a framework for modeling hippocampal contributions to generalization Learning transferable visual models from natural language supervision

Reference 25

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Observation 4cb7dd85-af67-481f-af53-66d0318df2f6 · outbound

This paper cites Getting aligned on repre- sentational alignment.Transactions on Machine Learning Research, 2025.

Data augmentation as a framework for modeling hippocampal contributions to generalization Getting aligned on repre- sentational alignment.Transactions on Machine Learning Research, 2025

Reference 26

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Observation 996a70bb-0487-4892-a932-4337ebd43f81 · outbound

This paper cites Human alignment of neural network representations.

Data augmentation as a framework for modeling hippocampal contributions to generalization Human alignment of neural network representations

Reference 27

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source=pdf_text observed=2026-08-06T00:25:19.900471Z digest=sha256:4b5d655af3cec74b26a964c8425157b7f883a5147f8955fd5db2b759eeb61270

Observation f7609862-d368-4174-963e-78c075ff38ec · outbound

This paper cites Human-level 3d shape perception emerges from multi-view learning.arXiv preprint, 2024.

Data augmentation as a framework for modeling hippocampal contributions to generalization Human-level 3d shape perception emerges from multi-view learning.arXiv preprint, 2024

Reference 28

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Observation 8a6c8394-fd6a-4692-8c52-e3d78fa6994e · outbound

This paper cites A is B” fail to learn “B is A.

Data augmentation as a framework for modeling hippocampal contributions to generalization A is B” fail to learn “B is A

Reference 29

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Observation 2fe8a1ef-6fe9-4370-b991-507c40334f08 · outbound

This paper cites Reverse training to nurse the reversal curse.

Data augmentation as a framework for modeling hippocampal contributions to generalization Reverse training to nurse the reversal curse

Reference 30

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source=pdf_text observed=2026-08-06T00:25:20.066954Z digest=sha256:ae8b63b4237a5acc2e23adbed8659e994644c07aa3c5f735d15d251a0e2c18c2

Observation 3c2bc03e-2564-43e9-af03-f331d01de140 · outbound

This paper cites Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs.

Data augmentation as a framework for modeling hippocampal contributions to generalization Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs

Reference 31

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Observation 75606521-4fc4-462e-beb5-692e479f8987 · outbound

This paper cites On the generalization of language models from in-context learning and finetuning: a controlled study.

Data augmentation as a framework for modeling hippocampal contributions to generalization On the generalization of language models from in-context learning and finetuning: a controlled study

Reference 32

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Observation 78826b7b-34c2-4f25-aef6-7b1a1a806364 · outbound

This paper cites Deductive closure training of language models for coherence, accuracy, and updatability.

Data augmentation as a framework for modeling hippocampal contributions to generalization Deductive closure training of language models for coherence, accuracy, and updatability

Reference 33

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source=pdf_text observed=2026-08-06T00:25:20.335912Z digest=sha256:c215d4c7b0411d63339769d5a2e7d473d8fd3f98db9c1d15486838517da8ffc6

Observation 18822972-3afd-4643-bdfe-d6e0fbab59e0 · outbound

This paper cites Syn- thetic continued pretraining.

Data augmentation as a framework for modeling hippocampal contributions to generalization Syn- thetic continued pretraining

Reference 34

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source=pdf_text observed=2026-08-06T00:25:20.402787Z digest=sha256:ddc896a594e2a25320f99258680c1d3483ab3edd03ae12d7e3b5aeabf057239a

Observation 44c72f66-c5d8-4385-8a1b-bd82e39a3101 · outbound

This paper cites New News: System-2 Fine-tuning for Robust Integration of New Knowledge.arXiv preprint arXiv:2505.01812, 2025.

Data augmentation as a framework for modeling hippocampal contributions to generalization New News: System-2 Fine-tuning for Robust Integration of New Knowledge.arXiv preprint arXiv:2505.01812, 2025

Reference 35

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source=pdf_text observed=2026-08-06T00:25:20.499378Z digest=sha256:af274324a80bb8b7bac8042dd45980cd3a74d41848f6fb8d618e5d224e4a3d67

Observation 975f9d3e-b7bb-4b79-abe7-f9e6c6fcef36 · outbound

This paper cites Data-efficient pre-training by scaling synthetic megadocs.arXiv preprint arXiv:2603.18534, 2026.

Data augmentation as a framework for modeling hippocampal contributions to generalization Data-efficient pre-training by scaling synthetic megadocs.arXiv preprint arXiv:2603.18534, 2026

Reference 36

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source=pdf_text observed=2026-08-06T00:25:20.564223Z digest=sha256:372b26b756824d5ec9e2624439fb69f96dd865b93a9560313f8e1178832f706f

Observation 10ca9c8b-be47-44cc-917d-38ca454dd704 · outbound

This paper cites Princeton University Press, 1954.

Data augmentation as a framework for modeling hippocampal contributions to generalization Princeton University Press, 1954

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source=pdf_text observed=2026-08-06T00:25:20.623908Z digest=sha256:11ecdd3aced8436ca30c36d2ccd55c47de488e56ae4f7adcce65e5391fd95b45

Observation b036e838-432e-4ba6-b331-662c10a56ec0 · outbound

This paper cites Edward Arnold, London, 1960.

Data augmentation as a framework for modeling hippocampal contributions to generalization Edward Arnold, London, 1960

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source=pdf_text observed=2026-08-06T00:25:20.699891Z digest=sha256:0922e60b53bad850c37f71ee4e6101ed43324cfb6b9e21135607595530d0c4a1

Observation 1d4f6070-00a5-4a8d-ab18-9bad1686f12d · outbound

This paper cites How computational modeling can force theory building in psychological science.Perspectives on Psychological Science, 16(4):789–802, 2021.

Data augmentation as a framework for modeling hippocampal contributions to generalization How computational modeling can force theory building in psychological science.Perspectives on Psychological Science, 16(4):789–802, 2021

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source=pdf_text observed=2026-08-06T00:25:20.801260Z digest=sha256:3dc4052ac9be01b5e0e4b5f9d2eee36c5db2b01bf146d8debc9170227d0ef1dd

Observation e4836c36-ca36-450b-be40-714a3af5d289 · outbound

This paper cites Using goal-driven deep learning models to understand sensory cortex.Nature Neuroscience, 19(3):356–365, 2016.

Data augmentation as a framework for modeling hippocampal contributions to generalization Using goal-driven deep learning models to understand sensory cortex.Nature Neuroscience, 19(3):356–365, 2016

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source=pdf_text observed=2026-08-06T00:25:20.870908Z digest=sha256:d309cd3733a1273d7fbc2b6b0504ba1e690e010bf55f5676f2793ce6a55a65f3

Observation 5410e1d1-8765-4cbf-b5df-005f1ebfae49 · outbound

This paper cites When the ventral visual stream is not enough: A deep learning account of medial temporal lobe involvement in perception.

Data augmentation as a framework for modeling hippocampal contributions to generalization When the ventral visual stream is not enough: A deep learning account of medial temporal lobe involvement in perception

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source=pdf_text observed=2026-08-06T00:25:20.949182Z digest=sha256:7f826efb01244f38bc1d6edf43109002ca997a95b1024f8b3db0f02598ef8fa6

Observation 07550a39-6259-42b1-9548-cd888620c4c7 · outbound

This paper cites Latent learning: episodic memory complements parametric learning by enabling flexible reuse of experiences.Transactions on Machine Learning Research, 2026.

Data augmentation as a framework for modeling hippocampal contributions to generalization Latent learning: episodic memory complements parametric learning by enabling flexible reuse of experiences.Transactions on Machine Learning Research, 2026

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source=pdf_text observed=2026-08-06T00:25:21.035556Z digest=sha256:274b5103bde94e0b02e8fdd610dd93605d60259e15119304b7d28db48a3f4618

Observation 1ae7e1d9-67dd-4e43-9b3c-fa52df136375 · outbound

This paper cites Improving latent generalization using test-time compute.3rd Conference on Language Modeling, 2026.

Data augmentation as a framework for modeling hippocampal contributions to generalization Improving latent generalization using test-time compute.3rd Conference on Language Modeling, 2026

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source=pdf_text observed=2026-08-06T00:25:21.086257Z digest=sha256:dc632a8bbdfab1aa0ab472814e9a34c9c981712063b5e4ced0f57443e2b82c4a

Observation 1920b69c-942a-4296-b4fe-90374e195cb0 · outbound

This paper cites Chain-of-visual-thought: Teaching vlms to see and think better with continuous visual tokens.arXiv preprint arXiv:2511.19418, 2025.

Data augmentation as a framework for modeling hippocampal contributions to generalization Chain-of-visual-thought: Teaching vlms to see and think better with continuous visual tokens.arXiv preprint arXiv:2511.19418, 2025

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source=pdf_text observed=2026-08-06T00:25:21.104924Z digest=sha256:caa53ba3d6a99651d84cbf23cf13ab606f7775b3b376d83327cca75b7065914c

Observation 6f931824-020f-4dcc-a548-06bb9e63a773 · outbound

This paper cites Perception Tokens Enhance Visual Reasoning in Multimodal Language Models.

Data augmentation as a framework for modeling hippocampal contributions to generalization Perception Tokens Enhance Visual Reasoning in Multimodal Language Models

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source=pdf_text observed=2026-08-06T00:25:21.143352Z digest=sha256:8fc2236e424d5b0422d78ba0ee437550f5c351f52657ef70a82d948aa8ee2cb4

Observation 0dbe2eec-7db0-40f2-a2f1-f0e9e21bb53d · outbound

This paper cites Flexible weighting of diverse inputs makes hip- pocampal function malleable.Neuroscience Letters, 680:13–22, 2018.

Data augmentation as a framework for modeling hippocampal contributions to generalization Flexible weighting of diverse inputs makes hip- pocampal function malleable.Neuroscience Letters, 680:13–22, 2018

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source=pdf_text observed=2026-08-06T00:25:21.199245Z digest=sha256:8a2350181bc52aae32f6c634e90be66ee410e3989c96bf3352ef348d6ff0b313

Observation bd3a4b5c-b5a6-4ea9-8aa4-227f48902878 · outbound

This paper cites Human replay spontaneously reorganizes experience.Cell, 178(3):640–652, 2019.

Data augmentation as a framework for modeling hippocampal contributions to generalization Human replay spontaneously reorganizes experience.Cell, 178(3):640–652, 2019

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source=pdf_text observed=2026-08-06T00:25:21.266100Z digest=sha256:766ca9510ae080a1dfe8bdbdc62d884e40042358aafb17f314f81de5cc9e6d00

Observation 179e2113-e3af-4002-a143-29e8a7ed8301 · outbound

This paper cites Schema representa- tions in distinct brain networks support narrative memory during encoding and retrieval.elife, 11:e70445, 2022.

Data augmentation as a framework for modeling hippocampal contributions to generalization Schema representa- tions in distinct brain networks support narrative memory during encoding and retrieval.elife, 11:e70445, 2022

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source=pdf_text observed=2026-08-06T00:25:21.330989Z digest=sha256:537b3483201d87b910bb4a88918f48a40131d3782d0bb3772090d4b9574c8b58

Observation cb5d88f0-c793-4ef9-b1ae-94bae72098d4 · outbound

This paper cites Overlapping memory replay during sleep builds cognitive schemata.Trends in cognitive sciences, 15(8):343–351, 2011.

Data augmentation as a framework for modeling hippocampal contributions to generalization Overlapping memory replay during sleep builds cognitive schemata.Trends in cognitive sciences, 15(8):343–351, 2011

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source=pdf_text observed=2026-08-06T00:25:21.393972Z digest=sha256:ef6d71c6aad7c29297582cdf6681fe84aee5cc98a70407240f0fa69aec65f5b5

Observation 14096095-516a-412e-9426-cfa8b6ab6963 · outbound

This paper cites Generative replay un- derlies compositional inference in the hippocampal-prefrontal circuit.Cell, 186(22):4885–4897, 2023.

Data augmentation as a framework for modeling hippocampal contributions to generalization Generative replay un- derlies compositional inference in the hippocampal-prefrontal circuit.Cell, 186(22):4885–4897, 2023

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source=pdf_text observed=2026-08-06T00:25:21.494542Z digest=sha256:b158982816710e27c1edf81c1726c66b30dffd4966c8e445820ab9b0ffcc0009

Observation 6a5fb723-c490-4cfa-bdfb-42160bb214a0 · outbound

This paper cites Human hippocampal ripples coordinate planning sequences and compositional representations in neocortex.Nature Neuroscience, pages 1–11, 2026.

Data augmentation as a framework for modeling hippocampal contributions to generalization Human hippocampal ripples coordinate planning sequences and compositional representations in neocortex.Nature Neuroscience, pages 1–11, 2026

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source=pdf_text observed=2026-08-06T00:25:21.543837Z digest=sha256:54e9b952bd1549ff04365440032283f2bcea04ea4ac576b90c5af7dd58ad460b

Observation 0dd620b7-5c36-4821-af9d-cef04cfed926 · outbound

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Data augmentation as a framework for modeling hippocampal contributions to generalization Searching for semantic knowledge: A vector space semantic analysis of the feature generation task.Frontiers in human neuroscience, 13:341, 2019

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source=pdf_text observed=2026-08-06T00:25:21.647091Z digest=sha256:a572f63285f29a9a69f86ea9332df60827dad3913795d4f317e452aa23eea65f

Observation d21cf6a8-9dea-4676-93cc-735d58c57852 · outbound

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Data augmentation as a framework for modeling hippocampal contributions to generalization What learning systems do intelligent agents need? complementary learning systems theory updated.Trends in Cognitive Sciences, 20(7):512–534, 2016

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source=pdf_text observed=2026-08-06T00:25:21.721339Z digest=sha256:aaad9196b526e52bc3ed12a5a3b8318f7319758606dc7ee3826de9d7712dd875

Observation 05b7180c-cc54-4ec7-86ae-e465fccec4ce · outbound

This paper cites Reactivation of hippocampal ensemble memories during sleep.Science, 265(5172):676–679, 1994.

Data augmentation as a framework for modeling hippocampal contributions to generalization Reactivation of hippocampal ensemble memories during sleep.Science, 265(5172):676–679, 1994

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source=pdf_text observed=2026-08-06T00:25:21.816232Z digest=sha256:d767a090085029e83579507cb05436a60334dc3b9a9e0667e2e467217b6786e4

Observation 9c4f6c46-9f21-46aa-8aab-6f8a92faddaa · outbound

This paper cites Reverse replay of behavioural sequences in hippocampal place cells during the awake state.Nature, 440(7084):680–683, 2006.

Data augmentation as a framework for modeling hippocampal contributions to generalization Reverse replay of behavioural sequences in hippocampal place cells during the awake state.Nature, 440(7084):680–683, 2006

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source=pdf_text observed=2026-08-06T00:25:21.904474Z digest=sha256:0ee93c7ba042a30fcee28c0902ccda479a06eb61e058bc3dc24d304d2c7d24f8

Observation 0edac229-39eb-4d2f-a8f4-1da6ed99c1e6 · outbound

This paper cites Odor cues during slow-wave sleep prompt declarative memory consolidation.Science, 315(5817):1426–1429, 2007.

Data augmentation as a framework for modeling hippocampal contributions to generalization Odor cues during slow-wave sleep prompt declarative memory consolidation.Science, 315(5817):1426–1429, 2007

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source=pdf_text observed=2026-08-06T00:25:21.978749Z digest=sha256:2fce562b9193331010310d76dc70d35ca03690721b769406a58de82131bc47fd

Observation 62a78d69-d120-47a8-b0e2-9eb3fbdf235a · outbound

This paper cites Strengthening individual memories by reactivating them during sleep.Science, 326(5956):1079–1079, 2009.

Data augmentation as a framework for modeling hippocampal contributions to generalization Strengthening individual memories by reactivating them during sleep.Science, 326(5956):1079–1079, 2009

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source=pdf_text observed=2026-08-06T00:25:22.053015Z digest=sha256:7dc08cd3099e3aaee487ea8a45349d88d8d63b37075fa289f509f0b07a233fac

Observation 633886e0-38c0-4af0-8e2c-9c6a00dd5618 · outbound

This paper cites an unresolved cited work.

Data augmentation as a framework for modeling hippocampal contributions to generalization Unresolved cited work

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source=pdf_text observed=2026-08-06T00:25:22.152770Z digest=sha256:69a8b189e67f721b61459faeec9b707c6c0bb894df92b8a210bced006a9db292

Observation ba9c1c2c-be62-4e2c-ae8c-473de7c8384a · outbound

This paper cites Replay comes of age.Annual Review of Neuroscience, 40:581–602, 2017.

Data augmentation as a framework for modeling hippocampal contributions to generalization Replay comes of age.Annual Review of Neuroscience, 40:581–602, 2017

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source=pdf_text observed=2026-08-06T00:25:22.239098Z digest=sha256:1286623aa94dbdf2323467e12271ebad2f68ec516ea6b92298f2334496899d9f

Pith citing papers

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