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Paper Citation Record · LEDGER

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models

As of 22 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 2 inbound Pith citation observations for arXiv:2506.06008.

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

pith.paper-citation-record.v1
2506.06008 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:09:18.904384Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:17.276670Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T13:05:38.346684Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact1
  • verified fuzzy8
  • unresolved43
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b9d541f-e04c-4a15-9e3e-82817446353b · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.005415Z digest=sha256:1558b94708a6b2637bd18eee75d82675b8c550b23df24cab633cf85478878c2d

Observation be3516a7-98c0-489d-a9d1-1fd1c3c32e17 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Piqa: Reasoning about physical commonsense in natural language

Reference 2

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no resolver link, observed 2026-08-07T06:09:18.014775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.014775Z digest=sha256:b398b63aa44be96a008ad0fe195559a6d81387342fc2a5d9ab397f64cb5ee9af

Observation 3d58bc4a-6dbc-4369-aaae-82a6e8c60dc4 · outbound

This paper cites Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Reference 3

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no resolver link, observed 2026-08-07T06:09:18.069910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.069910Z digest=sha256:cc007dfe266422832b8686e8b9df27b07e6d0543f8ea2f7f615c2c528fa6359f

Observation 363d33c3-2812-47f7-a457-78b7564ab0f5 · outbound

This paper cites Large language model-driven meta-structure discovery in heterogeneous information network.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Large language model-driven meta-structure discovery in heterogeneous information network

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.439258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.192874Z digest=sha256:2d875010b2a125d100e82c21c3e4a98a918cd831d3709451b8dc7205d07f7a2d

Observation 82e8f705-71d5-433c-ad73-ff51de2d8c0d · outbound

This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 5

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no resolver link, observed 2026-08-07T06:09:18.319798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.319798Z digest=sha256:038fd2eeff28229bee1a8b33f67a6fdef2e2adf1796b197daa4578e70b255657

Observation 2bdd7e04-a82f-455d-a9b3-e3ba90f5761b · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.357582Z digest=sha256:5b6ad2ad5779da44cf1e319ed62a3b77deb1c60215b9fe80fb8bef548422f549

Observation f144698a-1b56-4a99-bf8a-5f148aea6d61 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Training Verifiers to Solve Math Word Problems

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.511833Z digest=sha256:f727e336d46fd1cc362477e14735e170aaf1517a5e2cc034b25c7766f5759d2c

Observation 7e46ac0a-10e5-4f5a-bb20-6db3d219524a · outbound

This paper cites The Llama 3 Herd of Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models The Llama 3 Herd of Models

Reference 8

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source=arxiv_source observed=2026-08-07T06:09:18.641061Z digest=sha256:48f9807cb3a9a4569827e017262630326c815f268578f8a7c069d5d288a9b2e0

Observation f01a0502-b872-4466-9691-9693debff4e6 · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Detecting hallucinations in large language models using semantic entropy

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.428239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.732380Z digest=sha256:2b921b2a9572965a0abeb82171fbde609052737a7ef786682b81e81018823e67

Observation 29f35a7b-dca8-468f-a76d-c5c13546c6e2 · outbound

This paper cites Controlling Linguistic Style Aspects in Neural Language Generation.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Controlling Linguistic Style Aspects in Neural Language Generation

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.744169Z digest=sha256:d8e975df8bf30753bb0d986bfff5fac126977a28cbf2b8bf02e1f2ad3dd52d60

Observation db3a57fb-a447-435b-a63a-c258525c90bd · outbound

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

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning

Reference 11

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.749129Z digest=sha256:dad7149b44d4442d651f9c53acb6a428bbcb20823500ca19eb64727a88aae4fd

Observation 7b77ef92-de1c-4e9e-9118-b07336a97d33 · outbound

This paper cites Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.754060Z digest=sha256:d43ff5d22f1ea05a7f50409b056a04878e23add77843f1de1f8d82be0929771b

Observation 3bdfb2a5-81ff-49af-9e46-c21fcf83efa7 · outbound

This paper cites FOLIO: Natural Language Reasoning with First-Order Logic.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models FOLIO: Natural Language Reasoning with First-Order Logic

Reference 13

Resolution
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no resolver link, observed 2026-08-07T06:09:18.758315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.758315Z digest=sha256:b6c24c61d9a0e621d6508e681dc7b9c4e33c8a6e284072709d57e1a543ade835

Observation 27ad4da7-e401-4834-88ce-949137ddeebb · outbound

This paper cites Training Large Language Models to Reason in a Continuous Latent Space.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Training Large Language Models to Reason in a Continuous Latent Space

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.762669Z digest=sha256:00171fc51d55741194bac2e52a0cab049530a2248288b64c4b8925e8ef754d46

Observation 9c75f581-75d0-4ab0-83fe-c5d59441d014 · outbound

This paper cites Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities

Reference 15

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no resolver link, observed 2026-08-07T06:09:18.768633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.768633Z digest=sha256:6357b201ee20679d3a7fc5a5e230363076cb39593e37a959fc53f95eb6f80aa4

Observation 0696fe37-6a7c-4012-be9e-f57bef12c6ed · outbound

This paper cites Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2

Reference 16

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no resolver link, observed 2026-08-07T06:09:18.772564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.772564Z digest=sha256:60b77c7d72f07fe05e70815761387fe82add37d6a70599952156182da47af973

Observation d37a0ee0-4872-4522-b557-1927ba285e25 · outbound

This paper cites Mistral 7B.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Mistral 7B

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.778899Z digest=sha256:eb0cc49b09789a8d11660e1b07cb728bab82f711f830e44b82e12b1b5f2c9c88

Observation 93b309fd-0019-4814-8f5e-ae63e4f89eea · outbound

This paper cites LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.782339Z digest=sha256:ac9d59916f080ebec4907d23de3fa7e13265eb27d9adbc8b33a5915ea6b1af61

Observation 0ab29201-f3bd-494b-8ac5-7d7b700e3e90 · outbound

This paper cites S., Reid, M., Matsuo, Y., and Iwasawa, Y.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models S., Reid, M., Matsuo, Y., and Iwasawa, Y

Reference 19

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no resolver link, observed 2026-08-07T06:09:18.786334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.786334Z digest=sha256:548e3ed21d39ea12f65842c467421b722c51c19c793464bae3baba94eee79d4c

Observation ca9a9e98-4dc8-4063-acbf-77e8c5fde89c · outbound

This paper cites Measuring Faithfulness in Chain-of-Thought Reasoning.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.790171Z digest=sha256:acffc387575319e6e372dcee30ee09c0fab0e7a15fc90a1562267aac108ef699

Observation 4b9a3ee6-0298-42a5-9de5-8bf90e3892af · outbound

This paper cites Contrastive Decoding: Open-ended Text Generation as Optimization.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Contrastive Decoding: Open-ended Text Generation as Optimization

Reference 21

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.793999Z digest=sha256:0398e35afefa96d2e1f768bcf55bb95a64b51e4f4f64be365355938a537750e1

Observation ccab81b3-affc-4f89-abde-dc0d11258870 · outbound

This paper cites Chain of Thought Empowers Transformers to Solve Inherently Serial Problems.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Chain of Thought Empowers Transformers to Solve Inherently Serial Problems

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.797846Z digest=sha256:6eebd377690b28ec071a4f3f9cc7852b49b7a2d811dbb4936937179d6af2302c

Observation 0539741c-71f3-4baf-8a1a-1e7beceaf4d8 · outbound

This paper cites Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse

Reference 23

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no resolver link, observed 2026-08-07T06:09:18.801709Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.801709Z digest=sha256:1e7b628b06f36e46e9f98f0b9d4ee7072359ea958811a7760aa57c1a59b5b814

Observation 8d4fb08f-89ef-4ae4-aa5c-c40c66adfab0 · outbound

This paper cites Tuning Language Models for Robust Prediction of Diverse User Behaviors.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Tuning Language Models for Robust Prediction of Diverse User Behaviors

Reference 24

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verified exact
local_arxiv, observed 2026-08-07T06:09:19.108021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.805224Z digest=sha256:b4211392886b6e937cb337ace7122d9047c2c11216091bbe0d470cf27c4bd1b0

Observation b7d19ac7-6076-4584-a2ae-f741de9dd2f3 · outbound

This paper cites Learning to reason with llms, 2024 a.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Learning to reason with llms, 2024 a

Reference 25

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raw_fallback, observed 2026-08-07T06:09:19.402254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.808264Z digest=sha256:72da9305bc95cc5f0edf54831f398937d79a71e467b5e927ab0a8337f53e7508

Observation 6ee8aaa5-214a-493a-9072-1ee296aec8c4 · outbound

This paper cites Hello gpt-4o, 2024 b.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Hello gpt-4o, 2024 b

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.388879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.811438Z digest=sha256:3f26d7eafa774cdf7f1e858733e2526cfa5093b8e45b08e925a6e75a62e8c361

Observation 8a1e9201-a555-4784-9b4d-594212cd067a · outbound

This paper cites Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.814824Z digest=sha256:5359dc7a125d28a6cbe519be8d2bdbf65fe4381b2b6b94789865cc14c4bce336

Observation 41c1fd2b-052f-4471-aa6b-e4cc21cdf4df · outbound

This paper cites Language models are unsupervised multitask learners.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Language models are unsupervised multitask learners

Reference 28

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no resolver link, observed 2026-08-07T06:09:18.818148Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.818148Z digest=sha256:cc1c86b4120950f3ca28889114b7303fce2aa62a442a696f1e736cd57793c5d3

Observation 9cff6f0e-9aec-46d8-9443-aa86b1cea90a · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 29

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source=arxiv_source observed=2026-08-07T06:09:18.821931Z digest=sha256:3a9b8c80aa92c63a72b694bc16501e0b12f9beb8a3d66a3daf6ad6289e1da9a4

Observation 03771810-450a-414b-8672-ad354d0aacab · outbound

This paper cites Solving General Arithmetic Word Problems.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Solving General Arithmetic Word Problems

Reference 30

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no resolver link, observed 2026-08-07T06:09:18.825689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.825689Z digest=sha256:6c953d6eda88ffb9df6cf74c8ba9fadc72bc35e926ad177e62bb77b6605ecda7

Observation 14eb582e-1bd9-4b35-a8e2-daa853cce09c · outbound

This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models SocialIQA: Commonsense Reasoning about Social Interactions

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.830143Z digest=sha256:c4403aab4db3a524380739e6b73278cada2a3f236dd07b0cad1ee432b0381933

Observation 13757d55-b4a4-4aeb-a828-f4ee582b6180 · outbound

This paper cites Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models

Reference 32

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source=arxiv_source observed=2026-08-07T06:09:18.833058Z digest=sha256:d7b128ebecb6da6e9c4542bcedc7bbf577389e538f5168d3ce99a55e2101f5a9

Observation f88edfd0-9f00-4ec7-88aa-0855912b4c08 · outbound

This paper cites AgentSquare: Automatic LLM Agent Search in Modular Design Space.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models AgentSquare: Automatic LLM Agent Search in Modular Design Space

Reference 33

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no resolver link, observed 2026-08-07T06:09:18.836505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.836505Z digest=sha256:62a682f207d0b5ba32dc19e5f6e66c14ba76c6aac77ea9fd485247cd5c6717ec

Observation 0ef05f64-011c-48b3-9756-e3cf77153e9a · outbound

This paper cites Chain-of-Planned-Behaviour Workflow Elicits Few-Shot Mobility Generation in LLMs.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Chain-of-Planned-Behaviour Workflow Elicits Few-Shot Mobility Generation in LLMs

Reference 34

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no resolver link, observed 2026-08-07T06:09:18.840547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.840547Z digest=sha256:8e998eb755f2099744fe083947143e34a8c2a52271eaddee874c00fb97393f1e

Observation 8482694b-7698-4b21-9f12-55abe4730d9f · outbound

This paper cites Division-of-thoughts: Harnessing hybrid language model synergy for efficient on-device agents.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Division-of-thoughts: Harnessing hybrid language model synergy for efficient on-device agents

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.365406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.844176Z digest=sha256:6bdf7955dd07810a2fbb7a84bb716c1a3eb3bdd1b52661be75874992dec17723

Observation 50beabad-a179-4c42-9336-2dd27e8de991 · outbound

This paper cites Trusting Your Evidence: Hallucinate Less with Context-aware Decoding.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Trusting Your Evidence: Hallucinate Less with Context-aware Decoding

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.847845Z digest=sha256:2fa5b64db463e6e5ef8ddaf66452a458c8017963313a199d246a00cd104dc379

Observation 207995a8-b04d-4c37-8c73-2a79e8035db4 · outbound

This paper cites MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning

Reference 37

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no resolver link, observed 2026-08-07T06:09:18.851653Z

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source=arxiv_source observed=2026-08-07T06:09:18.851653Z digest=sha256:8d9f453e5892eb53ef7e46f3699681a5f57e76178517c3225f02f9f570ae5cd8

Observation e0b9de13-2f35-481f-b8e4-7fa1e17b55b8 · outbound

This paper cites To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

Reference 38

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no resolver link, observed 2026-08-07T06:09:18.855178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.855178Z digest=sha256:bb99eb6cb54e46cda887f0984e3e84732d0c040aa99ba09ee54987bc8a9f0dd2

Observation e04cc527-abe2-43ff-9660-420c23bb45e4 · outbound

This paper cites CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Reference 39

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no resolver link, observed 2026-08-07T06:09:18.859031Z

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source=arxiv_source observed=2026-08-07T06:09:18.859031Z digest=sha256:0d876925b2da144f4047372026bda51de90de1a0ed883220eb901fff7a78a03f

Observation 982b663b-5fcc-49f4-b1f0-a8305621400b · outbound

This paper cites Diverse beam search for improved description of complex scenes.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Diverse beam search for improved description of complex scenes

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.347763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.862224Z digest=sha256:d95a2cebc7f9225d7c0f317eed75c9b6961cae1928bce322674d1f6ff6833bab

Observation baf7a07b-7520-4b4b-ad2f-faac2d4e86b9 · outbound

This paper cites Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 41

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no resolver link, observed 2026-08-07T06:09:18.865615Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T06:09:18.865615Z digest=sha256:5701ec68b1fdb5e83883ffe32d8dab255944828982555c15a1fc5671c3656559

Observation 4cc3a0a0-4e42-4d9d-ac3c-7333afca9e9e · outbound

This paper cites Chain-of-Thought Reasoning Without Prompting.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Chain-of-Thought Reasoning Without Prompting

Reference 42

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no resolver link, observed 2026-08-07T06:09:18.869124Z

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source=arxiv_source observed=2026-08-07T06:09:18.869124Z digest=sha256:c03a448644b94bd66043f9e13879b2a6cde6cd4277f9c3b933459363928a13c1

Observation 03902df1-ae8e-4370-8dd6-5e8efcf372a2 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 43

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T06:09:18.872734Z digest=sha256:8ef1e8a0075896e7163c729c597966481f165b221e0c533ff2233efdf2ba72fd

Observation 4cd71fbd-38f1-4b25-b4fa-00e04ce81260 · outbound

This paper cites A., Beltagy, I., et al.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models A., Beltagy, I., et al

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.325765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.876383Z digest=sha256:82999d58803129bc22f06783a7207ad250cba8a34a279f0b53f65bd58dc43dec

Observation 66743bf4-4f95-4e58-be44-c889d7436f02 · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 45

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no resolver link, observed 2026-08-07T06:09:18.879081Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T06:09:18.879081Z digest=sha256:59109692d345b6e887984965b52f02128420ff92fd9ebeb8ac8971623bc13cbb

Observation b47fc467-91ab-4096-acc2-a3339d0ba436 · outbound

This paper cites V., Zhou, D., et al.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models V., Zhou, D., et al

Reference 46

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unresolved
no resolver link, observed 2026-08-07T06:09:18.882533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.882533Z digest=sha256:fa85e07860198f1f563b619349b18c7d5a4a3cd9efbf7e654ce1bd42a7c74f32

Observation 615b0461-5d23-44db-8080-3f153aee8bf5 · outbound

This paper cites The spearman correlation formula.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models The spearman correlation formula

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:09:19.301443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T06:09:18.886326Z digest=sha256:b5fb452e50a0693317d7cc3e5d411222f3da7ebff2578b301c0feb4d09ba93c6

Observation 9af2bd47-9f7b-4f8e-ac6b-95b6d8793e26 · outbound

This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 48

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no resolver link, observed 2026-08-07T06:09:18.889140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.889140Z digest=sha256:f7adcaf930473aef315f89e328a3b3ce21bc5c9a9ea22283e77a399b8ece1a6a

Observation 750a8af5-2a8e-4133-9a07-86c04b298095 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Tree of thoughts: Deliberate problem solving with large language models

Reference 49

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no resolver link, observed 2026-08-07T06:09:18.892266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.892266Z digest=sha256:103b8dd208e51c86b722d32204916a8931ae457945922856a5983debbfcb3520

Observation 979de358-7b98-48f3-a05c-8e4bb7c463f0 · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models Automatic Chain of Thought Prompting in Large Language Models

Reference 50

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no resolver link, observed 2026-08-07T06:09:18.898118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.898118Z digest=sha256:2786eb43af95fb4df668643c9acbdaf71830bc7e5853ef314edb351ec68e553e

Observation 5e48c119-0629-4f5a-8bfa-b655e45f50ab · outbound

This paper cites AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Reference 51

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no resolver link, observed 2026-08-07T06:09:18.900758Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.900758Z digest=sha256:214f65cfb91196bc7311390fe30e61bee70854715dd1e4fdc17da786542bbf5e

Observation 4f457ca4-7323-4443-91e4-54b429d1d5af · outbound

This paper cites write newline.

Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models write newline

Reference 52

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no resolver link, observed 2026-08-07T06:09:18.904384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:09:18.904384Z digest=sha256:35c16d4f7eb1f7c7b90e2ffddbd89420c890285272343a347993ddbd0fa29528

Pith citing papers

Observation 4e87dd64-f3a8-4d8c-8dc8-139296ce0f1a · inbound

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey cites this paper.

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models

Reference 112

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no resolver link, observed 2026-08-06T17:54:17.276670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:54:17.276670Z digest=sha256:1bead206b2603abcbd7d2ca5ff4b27c6932ef9310ef69448ce5df5216923c2c6

Observation 450733c3-4277-4466-9f9c-c87fa3680c09 · inbound

The Stepwise Informativeness Assumption: Why are Entropy Dynamics and Reasoning Correlated in LLMs? cites this paper.

The Stepwise Informativeness Assumption: Why are Entropy Dynamics and Reasoning Correlated in LLMs? Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models

Reference 16

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verified exact
arxiv_id, observed 2026-05-15T13:05:38.349029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T13:05:26.484571Z digest=sha256:a3380e0bbcec3288786b1abebd3ee05202dfc9cb9612752e8777991a7fdf2809