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Paper Citation Record · LEDGER

Temporal Sampling for Forgotten Reasoning in LLMs

As of 10 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 4 inbound Pith citation observations for arXiv:2505.20196.

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

pith.paper-citation-record.v1
2505.20196 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:02:26.048992Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:15:42.129693Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:46:45.680966Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved36
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70c7d326-6ed9-42ec-8b8a-8e847eef9652 · outbound

This paper cites Integer partitions.

Temporal Sampling for Forgotten Reasoning in LLMs Integer partitions

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:30.715168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.033707Z digest=sha256:9f14d06f72e078d3d7d21f51d15650a3461a2eee225bb7565fca3ce14fce4c94

Observation b58ca41b-2f50-4d3f-9051-996ee7f081f4 · outbound

This paper cites Training data attribution via ap- proximate unrolled differentiation, 2024.

Temporal Sampling for Forgotten Reasoning in LLMs Training data attribution via ap- proximate unrolled differentiation, 2024

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:30.550097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.212127Z digest=sha256:f8cd87419181a46e280cfa402ae992580c4c2da0c868b0a71393aa47a4b1d8d9

Observation f1d73099-f6cb-4f40-bdda-3fbace0b557a · outbound

This paper cites Scaling test-time compute with open models, 2024.

Temporal Sampling for Forgotten Reasoning in LLMs Scaling test-time compute with open models, 2024

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:30.356784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.225463Z digest=sha256:a59935463daa34e0dce1d0af3a116f2e7990f7096309d36f2b82b303b8270288

Observation 81dbd395-e89d-4511-98d7-c0b38b1f18a9 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Temporal Sampling for Forgotten Reasoning in LLMs Evaluating Large Language Models Trained on Code

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.236891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.236891Z digest=sha256:7b75cc93a732093da290c3c4b333141c33090db5a07716161f64d0eb91ba7bfd

Observation 3f4d909d-ed34-41c0-9570-218f75d6e845 · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.255182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.255182Z digest=sha256:a849fa8626fd97f0f23306f32804fab621eb94f4e9cb239b74147bd35924e65e

Observation 6cbad9c1-eb11-40ca-889d-78304facee2d · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Temporal Sampling for Forgotten Reasoning in LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.278184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.278184Z digest=sha256:670e5462d08744f2228bf8d599afbe8291be9630240a06f8459c97d3c3f4dccf

Observation 33929f6c-0c68-4ef9-90b7-e98e1714adb1 · outbound

This paper cites Raft: Reward ranked finetuning for generative foundation model alignment, 2023.

Temporal Sampling for Forgotten Reasoning in LLMs Raft: Reward ranked finetuning for generative foundation model alignment, 2023

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.326108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.326108Z digest=sha256:dfac9cd93ce0b447981d0ae777f77486d14d8e9f98631532346fbf0ea6517ee7

Observation 993a767d-68e2-4c37-a1b7-6fda07f280b8 · outbound

This paper cites Open r1: A fully open reproduction of deepseek-r1, January 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Open r1: A fully open reproduction of deepseek-r1, January 2025

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.348367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.348367Z digest=sha256:57335cc7a6469384917b92e0fe24f31d28f0ee0baf8aed87df0fa408a8a233df

Observation 1aa825a2-6d8e-4e56-acd4-544464a942b3 · outbound

This paper cites Alphazero-like tree-search can guide large language model decoding and train- ing, 2023.

Temporal Sampling for Forgotten Reasoning in LLMs Alphazero-like tree-search can guide large language model decoding and train- ing, 2023

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:30.139456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.354897Z digest=sha256:25fd28bab1295689d95dbb0e033abc95a64a35b90c7c5981984cc55ea13450f9

Observation a87407a6-5a1b-47d8-90b2-5c4e5ede8085 · outbound

This paper cites Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024.

Temporal Sampling for Forgotten Reasoning in LLMs Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.407754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.407754Z digest=sha256:9db368a8489fa1e3358e1d3fb1695ce0988419bfe785bd46a053f7b127bd939d

Observation b3289dfd-8af4-467b-9f42-3d59977b2626 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

Temporal Sampling for Forgotten Reasoning in LLMs Measuring mathematical problem solving with the math dataset

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:29.947899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.462345Z digest=sha256:eb29f3213bef1851313573f61194bb1039067f56514dc0ca525b4673e3a382fd

Observation a1bf7707-3401-47dc-9471-91ed35b4bde4 · outbound

This paper cites Measuring mathematical problem solving with the math dataset, 2021.

Temporal Sampling for Forgotten Reasoning in LLMs Measuring mathematical problem solving with the math dataset, 2021

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.533322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.533322Z digest=sha256:e3a279f79d926a35c33c713eada92b3fee9ae79914e9bbafbae24853c4b9ab3c

Observation ef3c62b9-eb3c-4942-a79a-974e89f82677 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Temporal Sampling for Forgotten Reasoning in LLMs Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.578889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.578889Z digest=sha256:790e6fafc183ce320ac4fadc3971c87cd70ae98101e72dc1f7c436664a4289af

Observation a2e60e65-9036-4a98-9c22-06a46cf996f4 · outbound

This paper cites Putting rl back in rlhf.

Temporal Sampling for Forgotten Reasoning in LLMs Putting rl back in rlhf

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:29.719136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.647588Z digest=sha256:03b9c6ec8a749472259c432e7e7a6074750f7769971481345da1bc47c3562ca0

Observation 472600c0-b3eb-48a1-bd36-5029bd3c87da · outbound

This paper cites Ii-thought : A large-scale, high-quality reasoning dataset, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Ii-thought : A large-scale, high-quality reasoning dataset, 2025

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:29.525687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.700807Z digest=sha256:0bc8349e11a3db85c10257f0f38c0b64a91378649f21d8bb8974e0df17bc4a01

Observation acc95381-6fa2-4f7a-9d6f-56fb86a2f5a3 · outbound

This paper cites Disentangling memory and reasoning ability in large language models, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Disentangling memory and reasoning ability in large language models, 2025

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:29.329756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.734235Z digest=sha256:e56c24254d586c447923d6175a5c759550a01b0863b75d30806e6513592d1791

Observation 1107fcfd-8811-4be0-ad73-2cdcc62c0af3 · outbound

This paper cites MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time.

Temporal Sampling for Forgotten Reasoning in LLMs MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.778999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.778999Z digest=sha256:55fce135b8085c0edfbf534bd65cdb6ad120ef734bf080fbd975b9c7a1fa2d54

Observation 972f01bc-f229-4add-80e5-48c92d350f2b · outbound

This paper cites Gunawi, Cody Hammock, Joe Mambretti, Alexander Barnes, Franc ¸ois Halbach, Alex Rocha, and Joe Stubbs.

Temporal Sampling for Forgotten Reasoning in LLMs Gunawi, Cody Hammock, Joe Mambretti, Alexander Barnes, Franc ¸ois Halbach, Alex Rocha, and Joe Stubbs

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:29.162314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.790451Z digest=sha256:4522185d55cb8ae86da4d87d04480d78d3d20e736a125837bf2f501c28bb36b6

Observation 104c28fe-9ff2-4000-a969-a137f8e40e68 · outbound

This paper cites ARGS: Alignment as reward-guided search.

Temporal Sampling for Forgotten Reasoning in LLMs ARGS: Alignment as reward-guided search

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:28.983441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.805177Z digest=sha256:0096da3e803151c4a9106019d9c3885a157658e92cf3f830df7d67dc4c5febe3

Observation 8f256095-4e90-40b5-841c-3c6d37bdc0e7 · outbound

This paper cites Kimi k1.5: Scaling reinforcement learning with llms, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Kimi k1.5: Scaling reinforcement learning with llms, 2025

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.808887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.808887Z digest=sha256:5660187da32b3bd68972a7227cdc13862287a86adec353dcbee62be68c34d5f1

Observation 13670720-9bab-4117-a955-facc318172a6 · outbound

This paper cites Fine-tuning can distort pretrained features and underperform out-of-distribution, 2022.

Temporal Sampling for Forgotten Reasoning in LLMs Fine-tuning can distort pretrained features and underperform out-of-distribution, 2022

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:28.794799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.812114Z digest=sha256:8e31678ecf6f1bad1c999aca8f74a7bb426e4cb15236b8043729a0351da10f41

Observation 9aa6ccff-3aa4-4725-a96d-c2c9504629ea · outbound

This paper cites Med-r1: Reinforcement learning for generalizable medical reasoning in vision-language models, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Med-r1: Reinforcement learning for generalizable medical reasoning in vision-language models, 2025

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:28.618669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.817008Z digest=sha256:a1c412777c4f9b60f73dbb472c8da570df5c4cbec0e1f3a368f3e256e3fe664e

Observation 12f2dc94-0fc4-498c-89a5-c05aed516231 · outbound

This paper cites Miranda, Alisa Liu, Nouha Dziri, Shane Lyu, Yuling Gu, Saumya Malik, Victoria Graf, Jena D.

Temporal Sampling for Forgotten Reasoning in LLMs Miranda, Alisa Liu, Nouha Dziri, Shane Lyu, Yuling Gu, Saumya Malik, Victoria Graf, Jena D

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:28.455123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:23.822902Z digest=sha256:6a0f597d46f03e4abf66a3bf6b9c0afe88d3309e3b203044aa7287ae6af3de63

Observation 72ccfa28-6238-4a10-ae52-8c334caa6385 · outbound

This paper cites Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica.

Temporal Sampling for Forgotten Reasoning in LLMs Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.875586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.875586Z digest=sha256:59e84399c7e0d3fcfc8937592e690d0ac708b66b4a43b0500b66ee24da2947b6

Observation b6d77920-7be7-466a-832b-afb1dcb2f8fb · outbound

This paper cites An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning.

Temporal Sampling for Forgotten Reasoning in LLMs An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.918480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.918480Z digest=sha256:c88f386e8fcdbfb2db221b54b2df510fe6f3c5e3065576e55c81120666108b6b

Observation d2aaa8f3-3bff-438d-87e5-5815c8ca0e76 · outbound

This paper cites Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation.

Temporal Sampling for Forgotten Reasoning in LLMs Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:23.966532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:23.966532Z digest=sha256:50ea01127a996ed3e463b24bc85354facbed1c72cb9905d9eaae4839d74ac0b1

Observation 1905c551-d608-4113-8cd8-7790aebe0100 · outbound

This paper cites s1: Simple test-time scaling, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs s1: Simple test-time scaling, 2025

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:28.276013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:24.037222Z digest=sha256:3c63b7e090eba99a92aaae468774f65b24a9629fdb00521bcebcb469b10b1470

Observation 2d0e710d-69c8-41cf-9fda-4ad4d47beb80 · outbound

This paper cites Sky-T1: Train your own o1 preview model within $450, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Sky-T1: Train your own o1 preview model within $450, 2025

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:28.063624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:24.112267Z digest=sha256:d23fac27eb78e164a4bd068f5ff484d67ce5dca7993c5c675dc46ec3a0cb6e9c

Observation b9bc2fbe-f3e7-4304-b74b-fff0dc7b390f · outbound

This paper cites Learning to reason with llms, 2024.

Temporal Sampling for Forgotten Reasoning in LLMs Learning to reason with llms, 2024

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:24.201176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:24.201176Z digest=sha256:84901b4c6b739f6a0833a9bff74fcb324009ec06f444bded5a1cccb680cc2a28

Observation 2f9da60b-9f49-4816-a93c-775a31a05115 · outbound

This paper cites an unresolved cited work.

Temporal Sampling for Forgotten Reasoning in LLMs Unresolved cited work

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:24.260758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:24.260758Z digest=sha256:f13b2906b692048006d77726285ccb61574be3ae9d0edefd03b6499bdc24d740

Observation af592150-0df5-4edf-820e-c8bc1f23ce90 · outbound

This paper cites Qwq: Reflect deeply on the boundaries of the unknown, 2024.

Temporal Sampling for Forgotten Reasoning in LLMs Qwq: Reflect deeply on the boundaries of the unknown, 2024

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:24.325870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:24.325870Z digest=sha256:9309219f7a4d050689967a9ad71cd43e3f660748534617e9c63331ccb0ebf05c

Observation d4c740ae-2096-464f-8864-134a332b86bc · outbound

This paper cites Manning, and Chelsea Finn.

Temporal Sampling for Forgotten Reasoning in LLMs Manning, and Chelsea Finn

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:24.399877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:24.399877Z digest=sha256:563f1b61ddbe8a80cac7a042cde42a7e925731ce1589a23bbc4ee05f684c1ec9

Observation f501025a-142a-42a5-8eff-922a8d511722 · outbound

This paper cites Gpqa: A graduate-level google-proof q&a benchmark.

Temporal Sampling for Forgotten Reasoning in LLMs Gpqa: A graduate-level google-proof q&a benchmark

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:24.459177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:24.459177Z digest=sha256:277f2f8a5fc06f8da43a1331fd65e11fda17b60b072a3eb93323611f313cee56

Observation 28b803aa-4298-4f9d-9fe7-4fb4d18550d3 · outbound

This paper cites Sutherland.

Temporal Sampling for Forgotten Reasoning in LLMs Sutherland

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:27.925285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:24.529300Z digest=sha256:f921da688fdeebf20cc7831853d36780654fdaa2998cee7365e76aae50df3c8c

Observation 8d41def4-9b7e-4cbc-bb7a-ac537e376c65 · outbound

This paper cites Sutherland.

Temporal Sampling for Forgotten Reasoning in LLMs Sutherland

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:24.572749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:24.572749Z digest=sha256:3046dab1e7078efb05cef8a2b4d54ee8e571e236ec1ea8f682e9d2050a29d545

Observation 70f60fbc-e06d-4e32-b444-53936710c085 · outbound

This paper cites Beyond chinchilla- optimal: Accounting for inference in language model scaling laws.

Temporal Sampling for Forgotten Reasoning in LLMs Beyond chinchilla- optimal: Accounting for inference in language model scaling laws

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:24.606601Z digest=sha256:2aef5b030ccd79176db2bfd85fb29da093bdb9450cdeb1c1ff53a999f8a6c351

Observation c9918e5a-a6c4-4331-99d6-5391077ce826 · outbound

This paper cites Proximal policy optimization algorithms, 2017.

Temporal Sampling for Forgotten Reasoning in LLMs Proximal policy optimization algorithms, 2017

Reference 37

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source=pdf_text observed=2026-08-07T14:02:24.624085Z digest=sha256:315c7c9f8c28d573f6c9928ee6135c979b64515c9dec2a54e663e2a7cd9f1888

Observation 19b5c516-05ad-4d02-8e36-d01d5821bb9d · outbound

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

Temporal Sampling for Forgotten Reasoning in LLMs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 39

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source=pdf_text observed=2026-08-07T14:02:24.655253Z digest=sha256:7e328158298d96cd14121fcde23dd2240d5ad3056210c9c670d7607802f9d9c0

Observation 4752f1da-0dcc-4cc6-9c09-fb0659d481a2 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

Temporal Sampling for Forgotten Reasoning in LLMs HybridFlow: A Flexible and Efficient RLHF Framework

Reference 40

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source=pdf_text observed=2026-08-07T14:02:24.661998Z digest=sha256:f9171b47b6fbce15a9028046ccc3a559799fb1e0680d13e2159686d623ae69b1

Observation 5916b830-5d57-41d5-9431-091656f01f16 · outbound

This paper cites Scaling llm test-time compute optimally can be more effective than scaling model parameters, 2024.

Temporal Sampling for Forgotten Reasoning in LLMs Scaling llm test-time compute optimally can be more effective than scaling model parameters, 2024

Reference 41

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source=pdf_text observed=2026-08-07T14:02:24.703763Z digest=sha256:c69d8bf05f39cc2862c1f791ce5b18fca9a6acf766876dc684940a097941fd25

Observation 4074a463-0208-4cc8-a4e3-287ed4a7c4d6 · outbound

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

Temporal Sampling for Forgotten Reasoning in LLMs Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 42

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source=pdf_text observed=2026-08-07T14:02:24.741475Z digest=sha256:b08ce4c16920ff79203ddd6b3cdc328adb86cc124d1c35a8b6d39079436f4023

Observation ce6846c5-ebcd-4d34-b4fe-f91e0e862b42 · outbound

This paper cites Open Thoughts.

Temporal Sampling for Forgotten Reasoning in LLMs Open Thoughts

Reference 43

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source=pdf_text observed=2026-08-07T14:02:24.795246Z digest=sha256:8e537f52554c5369620886361e6a91e466458e81bd47802f1e2448253680eb75

Observation 2be7d0f9-9174-43a8-944c-ed5d1bedd583 · outbound

This paper cites Still-3-1.5b-preview: Enhancing slow thinking abilities of small models through reinforcement learning.

Temporal Sampling for Forgotten Reasoning in LLMs Still-3-1.5b-preview: Enhancing slow thinking abilities of small models through reinforcement learning

Reference 44

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source=pdf_text observed=2026-08-07T14:02:24.880272Z digest=sha256:cad70cd6e48129ea1ff2dff5e676f1017d83e8bd4e21483706d048cf27b2ec8a

Observation 29fcc7dd-b9d0-411a-aa90-4bcfc9ae0e7c · outbound

This paper cites AlphaZero-like tree-search can guide large language model decoding and train- ing.

Temporal Sampling for Forgotten Reasoning in LLMs AlphaZero-like tree-search can guide large language model decoding and train- ing

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:27.559076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:24.927393Z digest=sha256:3e7540fbb2c608fa7310d359681037a890012e51c822d48ec50780b167823f8d

Observation 7add9d1d-1ae8-4a14-ad90-374c80687777 · outbound

This paper cites Self-consistency improves chain of thought reasoning in lan- guage models, 2023.

Temporal Sampling for Forgotten Reasoning in LLMs Self-consistency improves chain of thought reasoning in lan- guage models, 2023

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:27.393384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:24.991813Z digest=sha256:13d01887858646597dea64642b296f2a11bad887a5c3696a983afe17d0acb54f

Observation 36a8499f-50dc-45b3-8831-2af3aa08b01f · outbound

This paper cites Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou.

Temporal Sampling for Forgotten Reasoning in LLMs Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:27.208708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:25.038301Z digest=sha256:5bbe05af83ab531a2c825686e19421532940859eea4872e662bea753b38027f5

Observation c226b0a3-6021-4a39-af91-fc2e1a6689cb · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Temporal Sampling for Forgotten Reasoning in LLMs Chain-of-thought prompting elicits reasoning in large language models

Reference 48

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:02:25.093221Z digest=sha256:c512c6db77985a8c68bf9d10bdc272894d963fa0723426b0818f315599f9cd67

Observation 6d71cfd6-9692-45af-afb2-a02bee00383c · outbound

This paper cites SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution.

Temporal Sampling for Forgotten Reasoning in LLMs SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Reference 49

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source=pdf_text observed=2026-08-07T14:02:25.163164Z digest=sha256:0e3a46a5481382e436fad65734df85915daa9364f840784dfdcdebe0e1823f97

Observation da457912-d863-4163-89c3-00325bf822e2 · outbound

This paper cites Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models.

Temporal Sampling for Forgotten Reasoning in LLMs Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models

Reference 50

Resolution
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no resolver link, observed 2026-08-07T14:02:25.245487Z

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source=pdf_text observed=2026-08-07T14:02:25.245487Z digest=sha256:4ee12e3a4ef7c5dc678a701f8bc9f756270b45cbfd934105ee0a1b9ea2a5c24e

Observation b9b67ac5-083d-4e64-8dd4-c2e862a332bd · outbound

This paper cites Self-evaluation guided beam search for reasoning.

Temporal Sampling for Forgotten Reasoning in LLMs Self-evaluation guided beam search for reasoning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:27.034480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:25.291233Z digest=sha256:bb854ab640193491d5551964e1fb90c612fe91cd3adc9acd7c8b57ececa10b43

Observation 6dd1189b-63c8-4412-9700-dbe5dd2b0ffd · outbound

This paper cites DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data.

Temporal Sampling for Forgotten Reasoning in LLMs DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

Reference 52

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source=pdf_text observed=2026-08-07T14:02:25.377247Z digest=sha256:8c136112be71a30f5fd07bf26240822ca3ec4a797a8d13fc5c404ed452c84878

Observation c0775373-3000-4331-8586-bd6ebe95b757 · outbound

This paper cites A minimalist approach to llm reasoning: from rejection sampling to reinforce, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs A minimalist approach to llm reasoning: from rejection sampling to reinforce, 2025

Reference 53

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source=pdf_text observed=2026-08-07T14:02:25.436004Z digest=sha256:d9073f4724897412c098ff443092b15693b9cff63ec8d5eb410dd2d585170541

Observation abe6ad84-34cf-4ad5-8c2d-901d2f4ef843 · outbound

This paper cites Qwen2.5 Technical Report.

Temporal Sampling for Forgotten Reasoning in LLMs Qwen2.5 Technical Report

Reference 54

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source=pdf_text observed=2026-08-07T14:02:25.503406Z digest=sha256:6b106cb42e5810ee1e7ab1fb7b4b6be554e70c02eaa2f2ee6f8970a32e95a838

Observation 4c3c6752-3b80-4d13-8e8e-cb8b16671f30 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

Temporal Sampling for Forgotten Reasoning in LLMs Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 55

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source=pdf_text observed=2026-08-07T14:02:25.574892Z digest=sha256:581ec9c41f30017a5b8d9bace75c9d47a323209a23f017e177dd6f645d921c72

Observation 8114a1f2-929e-4e86-ba06-6ff428eded02 · outbound

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

Temporal Sampling for Forgotten Reasoning in LLMs Tree of thoughts: Deliberate problem solving with large language models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:26.852870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:25.648741Z digest=sha256:7c0e3c57d5072d64ef0a3e1efb5efbeef8d9030cdbfc475d5f97e9980fc7f3c4

Observation 94040b31-9160-44cf-b9f3-6c68bff61ae4 · outbound

This paper cites Dapo: An open-source llm reinforcement learning system at scale, 2025.

Temporal Sampling for Forgotten Reasoning in LLMs Dapo: An open-source llm reinforcement learning system at scale, 2025

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:26.693321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:25.707333Z digest=sha256:79d8b3a1d76846d763bfc06485862a74c9001ab5ce6051cd75bf7afd85a80681

Observation 1a42dcdf-bd3f-4522-b9c7-dd5234da1f4b · outbound

This paper cites Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?.

Temporal Sampling for Forgotten Reasoning in LLMs Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 58

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:02:25.765449Z digest=sha256:efd01c2808f54d5f74af9ac501fe84f2bccc34d0b11be0ad8d05072488bbdbbf

Observation 91b6be52-fabf-4aaa-b28b-d0dd78e3528c · outbound

This paper cites 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient.

Temporal Sampling for Forgotten Reasoning in LLMs 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient

Reference 59

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source=pdf_text observed=2026-08-07T14:02:25.839489Z digest=sha256:7bcfce673519e89a3f3d29e125c003303db66e3e8e347ff75f5ce36626df142c

Observation f4edee92-115a-49ab-b259-e47944d6d4f6 · outbound

This paper cites The Lessons of Developing Process Reward Models in Mathematical Reasoning.

Temporal Sampling for Forgotten Reasoning in LLMs The Lessons of Developing Process Reward Models in Mathematical Reasoning

Reference 60

Resolution
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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:25.907173Z digest=sha256:9bd38a981796060a7d81c114da997efaab91e3b88c48242de5916bb9f8fade8c

Observation 7edbab37-0923-45ff-bce5-125e33bfcb93 · outbound

This paper cites aha moments.

Temporal Sampling for Forgotten Reasoning in LLMs aha moments

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:02:26.472973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:25.976745Z digest=sha256:c65695cbfe99bcae0ea021e6f5967ab1af7c9b49fa4e5670c06b19797f8da0f6

Observation 7c3de85b-1c67-4e9b-bcce-648d4b99e51e · outbound

This paper cites N −Ci,j kj N kj # = (1− ri,j)kj Since Ci,j follows a binomial distribution B(N, ri,j), we have: E.

Temporal Sampling for Forgotten Reasoning in LLMs N −Ci,j kj N kj # = (1− ri,j)kj Since Ci,j follows a binomial distribution B(N, ri,j), we have: E

Reference 62

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T14:02:26.350525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:02:26.048992Z digest=sha256:cbe75ada89dc6669c889f2a060fa6e42e017ef6c33bd358f22082db45b990876

Pith citing papers

Observation caddb07a-2955-4f0f-b28c-415281230c70 · inbound

STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs cites this paper.

STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs Temporal Sampling for Forgotten Reasoning in LLMs

Reference 30

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no resolver link, observed 2026-08-07T15:15:42.129693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:15:42.129693Z digest=sha256:99e4711c43c2ebe945cae9dd449192ebe8815848eae65a7f9407ca2e01dbab57

Observation 89d42913-2226-4634-b56e-05c1653ec6c8 · inbound

First Return, Entropy-Eliciting Explore cites this paper.

First Return, Entropy-Eliciting Explore Temporal Sampling for Forgotten Reasoning in LLMs

Reference 15

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no resolver link, observed 2026-08-06T18:53:12.730408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:53:12.730408Z digest=sha256:2be24548c9c873fe3f85742068d81d238bf5aae882413b02484781d61269db2b

Observation ae2bbc0d-99d1-493b-9b4e-fc01be575a6d · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Temporal Sampling for Forgotten Reasoning in LLMs

Reference 293

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:02:24.794099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-18T00:02:24.352947Z digest=sha256:8ad7eb7ab0fd04446aadb4a1aa6f0c0f7a33173a02dfb24abf05d3d3b3f458f1

Observation 338ed308-9a1a-4c99-b8ab-634b9f73a7b8 · inbound

Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them) cites this paper.

Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them) Temporal Sampling for Forgotten Reasoning in LLMs

Reference 8

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verified exact
arxiv_id, observed 2026-07-02T07:46:45.682602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T06:48:28.788806Z digest=sha256:4fe97a7833f122f6d749f7890f6688425c8737e6f7df181fe410fb3117ea3abe