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Paper Citation Record · LEDGER

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2506.00396.

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

pith.paper-citation-record.v1
2506.00396 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:11:46.192441Z

measured 41 of 41 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

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f6377368-b056-412a-96ae-e14ccad40c31 · outbound

This paper cites URL: " 'urlintro :=.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively URL: " 'urlintro :=

Reference 1

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Observation 33a3c908-e5a4-4da1-9430-d564e72bd382 · outbound

This paper cites write newline.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively write newline

Reference 2

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source=arxiv_source observed=2026-08-07T12:11:41.847455Z digest=sha256:fbb20a031057d8e5a9cf3f66c98a5fef75bb1685aefede5ec9cb56d805090fa2

Observation f4499d80-d173-495d-aa62-b5e11faf4df3 · outbound

This paper cites Graph of Thoughts: Solving Elaborate Problems with Large Language Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Reference 3

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source=arxiv_source observed=2026-08-07T12:11:42.045200Z digest=sha256:289e1ab66e1a8b27f9d923c8b72ac51ab562bfb37b94bbb8b1eaf4c0cded4b8c

Observation a774c6f8-9cbb-4f70-a7eb-df45b99c2156 · outbound

This paper cites Accelerating Large Language Model Decoding with Speculative Sampling.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Accelerating Large Language Model Decoding with Speculative Sampling

Reference 4

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source=arxiv_source observed=2026-08-07T12:11:42.178654Z digest=sha256:d0e665f19aabd91b9a742c45107537e31a178cf69c9676ea4d51fbd271431b02

Observation cc94f70a-b3fa-48af-abc8-c7a354fcb0f0 · outbound

This paper cites FinQA: A Dataset of Numerical Reasoning over Financial Data.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively FinQA: A Dataset of Numerical Reasoning over Financial Data

Reference 5

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source=arxiv_source observed=2026-08-07T12:11:42.331835Z digest=sha256:1f260b3ae1fdf9f1a84476b48562ce1d55f5997bc6b2462a722b6b1256458c6a

Observation 7a086ed3-0756-41da-896f-065a4a73b3f6 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Training Verifiers to Solve Math Word Problems

Reference 6

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source=arxiv_source observed=2026-08-07T12:11:42.497773Z digest=sha256:52e838db8a8dc0833bc9b1d2c0582435c97a8fb24e2ef681d2951a3727fa9fb3

Observation 95746e22-c505-4434-a73e-f0f025859af1 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 7

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:11:42.637601Z digest=sha256:13fd032a0ab26601d32d28478a5c0c2ceac13f3f1de90518705fe5afa85c3c03

Observation 4bb8b3b9-fc0f-4f72-a8fd-e7e244cb4162 · outbound

This paper cites Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Reference 8

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source=arxiv_source observed=2026-08-07T12:11:42.761281Z digest=sha256:1409e3bc71d861f4b0072d5adf5d07da5ceb93c40e0611567fd3362075d796a1

Observation 4e2df33f-7c43-4e80-bbd8-fd38cc1f67d5 · outbound

This paper cites The Llama 3 Herd of Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively The Llama 3 Herd of Models

Reference 9

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source=arxiv_source observed=2026-08-07T12:11:42.881590Z digest=sha256:0e548adcad1b698ff91256c8928cf1d083cf8f18346e671e251284537ea5aea2

Observation 188d4c1d-6f1a-4d79-a559-54be10710330 · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Reasoning with Language Model is Planning with World Model

Reference 10

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source=arxiv_source observed=2026-08-07T12:11:43.039389Z digest=sha256:2524bac798234d17645e19eb178a1a5ed53ab9e94911bba7f04d6663b0109e71

Observation 75a67c94-5ce5-4074-bbb4-7174c7500b37 · outbound

This paper cites Large Language Models Cannot Self-Correct Reasoning Yet.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Large Language Models Cannot Self-Correct Reasoning Yet

Reference 11

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source=arxiv_source observed=2026-08-07T12:11:43.197324Z digest=sha256:efa7be7919798091bb5e500be3d6a746cb5f89a4e4829dfad8cf0fb9b0218cb9

Observation bb996b5b-de16-4817-a101-d0dafa3b1dfe · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 12

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:11:43.343195Z digest=sha256:38cea3a35d926eeb815d8f023b5d8f807aeb2d649d5297a0a40bf19afc3d3378

Observation cd972443-e59a-40ce-b06d-3303f40eea88 · outbound

This paper cites Reward Design with Language Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Reward Design with Language Models

Reference 13

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source=arxiv_source observed=2026-08-07T12:11:43.508406Z digest=sha256:7b0efd40db2712945a8c6d70302effdcb5b4dc4c8297fc5ec8185b22c4daae6c

Observation ac6ecb87-4432-4707-b893-a0045ec5f7c2 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 14

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 62239cb0-9347-4121-8d7d-05f951a4c1c9 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:11:43.827341Z digest=sha256:636626c77e3cbd172f4222d7bab4ee47af1232e7878ce106f315dc24171de778

Observation 73869741-03f6-4365-8c9b-9dc415079e0e · outbound

This paper cites GPT-4 Technical Report.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively GPT-4 Technical Report

Reference 16

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source=arxiv_source observed=2026-08-07T12:11:43.975924Z digest=sha256:09c38fcce347a3211c09992af5bcb17a7a5a21e784e38a219f09e64d3797d58b

Observation 4055b49f-ec1b-4352-84a0-f9ce9dd6a23b · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 17

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:11:44.122879Z digest=sha256:0db0af0672b86cb9c92eb9b40bd968b1a70ec2c50dd28652d2d5f9f23bd40062

Observation 49912d8b-c8cf-4072-bdc1-e0727f766815 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-08-07T12:11:44.221997Z digest=sha256:f600e85ca893c6676e82f222f281e1a3913145cce7dd33a48347009eca2e4956

Observation 65b26389-f98b-4547-aab2-6754cc213b0b · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 19

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source=arxiv_source observed=2026-08-07T12:11:44.370193Z digest=sha256:1ddcaebfe0f6e3b8bd04da01ad3dcc63b93e804a32bf8241279bda606c95e9da

Observation a4790b78-16e9-45ec-bb8b-b429c0fc16df · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 20

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Observation b9aaa710-1c47-41ed-9dd1-89d68d6435ff · outbound

This paper cites Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents

Reference 21

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Observation fdbd1863-aabd-4658-bf01-a14a595989a2 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 22

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Observation b52a0d0b-9606-428e-8a7f-0f4c3a020837 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-07T12:11:44.725755Z digest=sha256:1b23dd3f9b9a1a683e37cb40076132d2a07e2bacec1729142243de8dac2a185e

Observation 25ecfa1a-a068-49e0-beea-9488145e4ca5 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 24

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source=arxiv_source observed=2026-08-07T12:11:44.810602Z digest=sha256:917850c57387227aabdb190e788ed351ffbe7a9268dd6f54e9bcc15e5f14c057

Observation 54b69683-c3c1-46c1-919f-080e91e0a93d · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-07T12:11:44.904533Z digest=sha256:c90f6dd4f20ae78a33ffd59e2c3f80be41dc3527071ab4267481cfd66cabf268

Observation 20b8ee25-6ca8-437f-a48c-90b04c7aca29 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 26

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source=arxiv_source observed=2026-08-07T12:11:44.977819Z digest=sha256:ceb903e74745dd481446bf5f72f122fb82d9ae4ca4b07f0b0ba0680a977c74db

Observation 22ae8d7f-691c-417f-975f-b2e50f5f1b5c · outbound

This paper cites PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models

Reference 27

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Observation 06ebea2b-a996-450d-90de-d4a4cf82c051 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 28

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Observation 4dce3f3e-4cef-4567-9e38-923e7a5aaa63 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-07T12:11:47.282226Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 58fb2e04-6789-4528-ab20-838d42e59af2 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 30

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Observation 00d41d8c-0668-40df-9829-13e3d9fee315 · outbound

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

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 31

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Observation 22c6d246-76e5-403c-be61-4cca2e589cfc · outbound

This paper cites Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Reference 32

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source=arxiv_source observed=2026-08-07T12:11:45.444335Z digest=sha256:ec73f764e75a9680c99a293c9b2f8842c18c74fcf756a127f05e3245887e80e0

Observation c97218ba-3f3b-4c83-9e10-22a1c2722c86 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:11:45.475544Z digest=sha256:215b3de592dc8fb52059591792e1bc8333b1c0729b7a2eacb085cd50a1263abb

Observation 02aadac5-3a10-41c4-ab28-8da1516f555c · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 34

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:11:45.568213Z digest=sha256:6ccb8f175d195f7eb4343ff6d6527fe03a4a536edfce91a799c9d6bfeed64874

Observation 26fa552f-2b33-4684-9e9a-661ef3c1d765 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 35

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raw_fallback, observed 2026-08-07T12:11:47.096342Z

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.

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Observation 7e877f1d-7658-4cd9-8983-0f96efd48657 · outbound

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

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 36

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:11:45.751564Z digest=sha256:66170af278b40694e55c46e82298beaaff9377d3adf75ba7fc6115b1308c0d40

Observation 77ab271b-cb31-40fb-a81d-147fbdc2ca4a · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-07T12:11:46.962735Z

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=arxiv_source observed=2026-08-07T12:11:45.857180Z digest=sha256:f724a99f437d270e5a5428586c58c2df0c931cdf2c092768999b9ab623a103dd

Observation 5d01445e-2841-406d-808a-45f48acc6633 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T12:11:45.942978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:11:45.942978Z digest=sha256:88f2dc147a1104816f431e3f7317b587b22b537f242961e3342cce244ba140ff

Observation fb7fb42d-6cd0-4eca-a422-d9b0e69eddbf · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:11:46.019554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:11:46.019554Z digest=sha256:35d0a8640868a39f845d36c24c2155bb1d3dd0c0677279bf54d1b60717c13372

Observation 23584c56-45e1-40e6-a1e6-fb8c3a2c20d5 · outbound

This paper cites ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:11:46.100639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:11:46.100639Z digest=sha256:4c87b47a67f85c494805fee4fedae71e563b4b89ab32b677319eb23a4be5349d

Observation cb77b58f-2502-4520-af81-f354e4335d57 · outbound

This paper cites an unresolved cited work.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:11:46.822688Z

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=arxiv_source observed=2026-08-07T12:11:46.192441Z digest=sha256:83dd3d8c8aff4c51f6026a2cb6ae2bcd7a2899d3f421a8c7628ab19e018c9d09

Pith citing papers

No inbound Pith citation observations are available.