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Paper Citation Record · LEDGER

The pitfalls of next-token prediction

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2403.06963.

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

pith.paper-citation-record.v1
2403.06963 v3

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:37:13.051058Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T16:32:39.688341Z

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Outbound references

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Pith citing papers

Observation 593f5c8c-8f88-4c8f-a576-f9fdf44ec515 · inbound

Do Large Language Models Perform Latent Multi-Hop Reasoning without Exploiting Shortcuts? cites this paper.

Do Large Language Models Perform Latent Multi-Hop Reasoning without Exploiting Shortcuts? The pitfalls of next-token prediction

Reference 4

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source=arxiv_source observed=2026-08-12T12:53:38.715882Z digest=sha256:0e2de8ad209bb7923860b46751222b2acd9f937f6af55ba822d2dfe93ef0bf23

Observation b603b766-1b86-41f7-990f-f439f55ed1c4 · inbound

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers cites this paper.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers The pitfalls of next-token prediction

Reference 3

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source=pdf_text observed=2026-08-12T17:37:13.051058Z digest=sha256:240f97225e40e79f5ae54f9d56f6dd79e8bd6df7f560a7305cf8c34df91c18e2

Observation 7edaab7e-f345-40d9-b401-0fb1e5f3f1c7 · inbound

The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation cites this paper.

The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation The pitfalls of next-token prediction

Reference 1

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source=arxiv_source observed=2026-08-11T21:37:19.771484Z digest=sha256:e37e260796c091913b989306e1ad051a4b23137759bb1d203a6e2d3d5ed9400a

Observation 27ce0192-877a-4e95-9032-cefdc6c31409 · inbound

Transformers Can Navigate Mazes With Multi-Step Prediction cites this paper.

Transformers Can Navigate Mazes With Multi-Step Prediction The pitfalls of next-token prediction

Reference 2021

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source=pdf_text observed=2026-08-11T20:55:53.636817Z digest=sha256:3e1b81b28b2d1a59b6bf7e2af2afdab8bb4545ea5c95484970bab88d93b711a9

Observation b65cbd1a-4ec7-47a8-ba3e-774ec3dcbf54 · inbound

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation cites this paper.

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation The pitfalls of next-token prediction

Reference 15

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source=pdf_text observed=2026-08-11T20:53:23.652647Z digest=sha256:79db0723d293498ebabb48c121121fee42c172d2d4fdbd53a3442770f593f1d5

Observation b7fdaa3b-1ebb-432a-9ac8-b1208bc8b1c5 · inbound

Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation cites this paper.

Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation The pitfalls of next-token prediction

Reference 4

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source=arxiv_source observed=2026-08-11T15:47:21.160944Z digest=sha256:3a102c183ea8e3ff3bc22a74b9c0d3abb20a9b337bcabc96560eb383e3d9c6f7

Observation 97561df1-5048-4243-9e12-c5be7dc2f295 · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) The pitfalls of next-token prediction

Reference 13

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arxiv_id, observed 2026-05-18T04:33:39.793820Z

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source=pdf_text observed=2026-05-18T04:33:39.076517Z digest=sha256:00fe8f0abff8b0f2822896b54160f63723e32661798130ac4d6e780ccde4a388

Observation 425ebbd0-fd3c-4573-99d5-10b8f7e29ded · inbound

Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning cites this paper.

Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning The pitfalls of next-token prediction

Reference 2

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source=arxiv_source observed=2026-08-10T14:15:45.972771Z digest=sha256:2456531837986bc0b4ed5205a640e68ed2d197e1b5dc3192f8b1514a1a880c9d

Observation cab5567d-670c-4b5e-b055-b7933a0c1642 · inbound

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges cites this paper.

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges The pitfalls of next-token prediction

Reference 6

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source=arxiv_source observed=2026-08-09T14:54:29.092681Z digest=sha256:ad588ef39201d96407f25218506830a0faf0b8644a1a21f5d8ec4a18cc4444cf

Observation 8eccdc74-7ec0-406f-943e-f5ec5ff4c17b · inbound

Emergent Response Planning in LLMs cites this paper.

Emergent Response Planning in LLMs The pitfalls of next-token prediction

Reference 5

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source=arxiv_source observed=2026-08-08T16:18:47.960815Z digest=sha256:2a065cce7ca5ee68a7707e5a4c1b0439742e74d7d6442b75bc174e4401b8ae36

Observation e7f9712b-a369-4230-9193-2ed4236efd4f · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey The pitfalls of next-token prediction

Reference 6

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source=pdf_text observed=2026-08-07T14:11:50.713502Z digest=sha256:0efdc9eaeb9f9945039b9c75a34fb384322e60cd8319756a9d2268ba7c9d6930

Observation 29109999-bdad-4cb0-9c0b-2d873aa2b929 · inbound

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities cites this paper.

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities The pitfalls of next-token prediction

Reference 26

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source=pdf_text observed=2026-08-07T14:04:55.284361Z digest=sha256:0a6efcdb1c5db0d15a83508658485e4684c1bf9c06293836e109678ed66eafca

Observation 330aaa9c-2d26-4b5b-918f-12e2979f0f09 · inbound

Learning to Insert [PAUSE] Tokens for Better Reasoning cites this paper.

Learning to Insert [PAUSE] Tokens for Better Reasoning The pitfalls of next-token prediction

Reference 7

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source=arxiv_source observed=2026-08-07T11:06:16.894905Z digest=sha256:8f9f487a8beb180da40ddc0c8a5bae16d849a8d590f16047032f36840e454784

Observation 7bb6ceb4-7e4c-48e3-9b5c-12a1b4ca336c · inbound

Improving Large Language Models with Concept-Aware Fine-Tuning cites this paper.

Improving Large Language Models with Concept-Aware Fine-Tuning The pitfalls of next-token prediction

Reference 3

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source=arxiv_source observed=2026-08-07T05:28:23.808234Z digest=sha256:c01d888e4b605aaf321fcedd928db5bc8fc6126790ce15af2269cc59189f980f

Observation 1c1b743d-b5eb-483e-b48c-637472cb1aaf · inbound

Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks cites this paper.

Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks The pitfalls of next-token prediction

Reference 1

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arxiv_id, observed 2026-05-19T09:52:14.138276Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1e615873-8bf1-4611-866f-5ac7b65f19f1 · inbound

STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner cites this paper.

STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner The pitfalls of next-token prediction

Reference 27

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source=pdf_text observed=2026-08-06T22:40:00.827394Z digest=sha256:aede8958721a12dacd40d86e7388e9245629910fefb232a9da5cdb7f25e02d31

Observation 8e9b7589-c1b8-4059-a529-6b5e9fb8dab8 · inbound

DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models cites this paper.

DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models The pitfalls of next-token prediction

Reference 113

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Observation dbd17dd0-e8b6-48d2-8a91-a91f2b06f1e2 · inbound

From Reasoning to Super-Intelligence: A Search-Theoretic Perspective cites this paper.

From Reasoning to Super-Intelligence: A Search-Theoretic Perspective The pitfalls of next-token prediction

Reference 2025

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source=pdf_text observed=2026-08-06T18:02:50.296623Z digest=sha256:dc17309acd1b10441eb707b2062661f76bd91f4843867cc41eb06981d685a831

Observation e31c6bf9-64e2-4f0e-88ac-8c15ed9be742 · inbound

PIG-Nav: Key Insights for Pretrained Image Goal Navigation Models cites this paper.

PIG-Nav: Key Insights for Pretrained Image Goal Navigation Models The pitfalls of next-token prediction

Reference 11

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source=pdf_text observed=2026-08-06T14:59:05.045852Z digest=sha256:e6b84c70935912be611883b746b1e9062f62505a7a53e07fa25334250c78ac5f

Observation 90604a96-237f-4df6-bf34-a0414368a771 · inbound

What am I missing here?: Evaluating Large Language Models for Masked Sentence Prediction cites this paper.

What am I missing here?: Evaluating Large Language Models for Masked Sentence Prediction The pitfalls of next-token prediction

Reference 2

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source=arxiv_source observed=2026-08-05T21:58:16.306251Z digest=sha256:d8145320e1cf90200625dd3381ded2c9a1b29ac0efc509aa2d72d6f27319ded1

Observation a93dc9e0-f35b-4bc3-b1e2-242761814317 · inbound

Multi-Token Prediction via Self-Distillation cites this paper.

Multi-Token Prediction via Self-Distillation The pitfalls of next-token prediction

Reference 2

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arxiv_id, observed 2026-05-16T06:47:28.355132Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f3e13ea5-5a8c-45c6-8959-14dfebe2b2b9 · inbound

Noise is not always detrimental: the capacity of quantum batteries is enhanced in black holes cites this paper.

Noise is not always detrimental: the capacity of quantum batteries is enhanced in black holes The pitfalls of next-token prediction

Reference 3

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Observation fb1f1cc1-a7b0-4cfa-9481-069c09c701ab · inbound

Semantic Trimming and Auxiliary Multi-step Prediction for Generative Recommendation cites this paper.

Semantic Trimming and Auxiliary Multi-step Prediction for Generative Recommendation The pitfalls of next-token prediction

Reference 3

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arxiv_id, observed 2026-05-10T22:30:50.851078Z

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Observation 8f57c136-f7bf-4062-9c43-8d19c9af8292 · inbound

Pen-Strategist: A Reasoning Framework for Penetration Testing Strategy Formation and Analysis cites this paper.

Pen-Strategist: A Reasoning Framework for Penetration Testing Strategy Formation and Analysis The pitfalls of next-token prediction

Reference 6

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source=pdf_text observed=2026-05-08T17:48:09.078064Z digest=sha256:e691eb3ffe892ed681708f127f53f9da7992c37ce16aaa94745a907312a4dede

Observation a47ef29c-e75b-4ce3-8202-e0208ff101a4 · inbound

Continuous Latent Diffusion Language Model cites this paper.

Continuous Latent Diffusion Language Model The pitfalls of next-token prediction

Reference 3

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arxiv_id, observed 2026-05-11T20:11:10.814275Z

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source=pdf_text observed=2026-05-08T10:04:09.646578Z digest=sha256:65bc7ce02261dd97aeb20bdd7c2abe2bea24b183f7d3c4f58ea58b82438eb0b6

Observation 3d523ce9-26a9-4c95-8483-43f684b5f862 · inbound

Representation Without Reward: A JEPA Audit for LLM Fine-Tuning cites this paper.

Representation Without Reward: A JEPA Audit for LLM Fine-Tuning The pitfalls of next-token prediction

Reference 28

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arxiv_id, observed 2026-05-19T16:32:39.690750Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T16:27:51.512806Z digest=sha256:df4808e90dc46bc64e45be74aad35540712b06ee8202bdf44b0f8b149141c8bd

Observation 36c301e3-e3e2-4f76-b102-777b817fbdae · inbound

Hierarchical Domain Generalization cites this paper.

Hierarchical Domain Generalization The pitfalls of next-token prediction

Reference 158

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source=arxiv_source observed=2026-08-01T20:54:17.085738Z digest=sha256:5eebdb856152441176cfd8e379a9dacc3bd3665431a880aad441dbae3eba9e9d

Observation 15eccb68-e8ae-4a0d-b2af-0e07de6f6266 · inbound

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts cites this paper.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts The pitfalls of next-token prediction

Reference 22

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source=pdf_text observed=2026-08-02T10:39:43.469042Z digest=sha256:2822720c47090fb914013681ae90548fc739846dbd1c5c9c7f11abe9d80bb6b2

Observation 89dffa39-1203-4507-988a-72ab5b701be1 · inbound

DeepLook: Deeper Thinking with Lookahead cites this paper.

DeepLook: Deeper Thinking with Lookahead The pitfalls of next-token prediction

Reference 37

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source=arxiv_source observed=2026-08-02T11:32:12.716308Z digest=sha256:2d2d0765d73412ead1fed308bcb0e7233d812eb82c3a694f114b53bed89b9e45

Observation a55de02f-d124-4cbe-b45d-ea0d9dec4036 · inbound

WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA cites this paper.

WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA The pitfalls of next-token prediction

Reference 105

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source=arxiv_source observed=2026-08-06T00:41:01.894675Z digest=sha256:77bc56ddd02d0648a9e92321f11b44d4e450f791bf3a1458ef819f4b7dbfa666

Observation 732a77e5-9682-4c12-a6a6-557f96e0cbce · inbound

The Effect of Perceived Race and Gender on Police Language Use: Experimental Evidence from VR Simulations cites this paper.

The Effect of Perceived Race and Gender on Police Language Use: Experimental Evidence from VR Simulations The pitfalls of next-token prediction

Reference 18

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source=arxiv_source observed=2026-08-06T10:34:09.807924Z digest=sha256:0924d5e026e5d024f851b8588ba5a5041a388da97e8d8bfc53b9382e908da29e

Observation bc540637-b016-46d0-880c-8a6348e0c045 · inbound

Refining Over Resampling: Test-Time Self-Correction for LLM Reasoning cites this paper.

Refining Over Resampling: Test-Time Self-Correction for LLM Reasoning The pitfalls of next-token prediction

Reference 23

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source=arxiv_source observed=2026-08-08T05:05:24.726104Z digest=sha256:4195cd34da72e61ae279b60cfde31e16d12f123b80307c6fce038dd034c8168b

Observation abef9dd7-49ed-4618-92e1-8e8980398160 · inbound

Hierarchical Latent Prediction for Language Models cites this paper.

Hierarchical Latent Prediction for Language Models The pitfalls of next-token prediction

Reference 11

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source=arxiv_source observed=2026-08-07T23:13:07.281639Z digest=sha256:306930e3a7e4f7a6e2a2eeab50d9f6f508dc192e7deb4055cdff99c19ac9f396