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Paper Citation Record · LEDGER

Temporal Sampling for Forgotten Reasoning in LLMs

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.033707Z digest=sha256:b6f035fb36ee98e3e65a228e20cba69d0449f0bb150dd66f9350beceb4b9cbf1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.212127Z digest=sha256:cd28afd27a3dbe54638c5d86d81a678c1c55479e4b0b514780be4df7a3c5d787

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.225463Z digest=sha256:76f2e99ed0b7af05cdb4de93d928263b8ec559eb6b11ebfe4df37a1bfea121cb

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=sha256:6723a068f0bfe44773deb70012ceda656913102c849b3f01e848cad92f63b18f

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=sha256:8788bbe89a5aeec7b49da01d36a3934a5b9f7e82f7d93fc608cd138cefecdbf0

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=sha256:60da945f88d539a4a23cfe1a92bbc8f2a7caa258201c3132dec3f4bb3696f3f1

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=sha256:20b94e74a9c21be2670ad7b5d10ec9cad4496feb64684e6125f441e874e8e77b

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=sha256:3cdcfc53c979f9211ae672a9112aa364fb7c209ac02820e6e5b29bb107d533be

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.354897Z digest=sha256:382dec913f951b0e063a3772bf944ee077020b5e0c9829c231bf6037a24c7eb4

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=sha256:2c9d4175e424a0342bb9066b2b1dd5aa4c6d1dec1578b39d0ff5b1c66f03a389

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.462345Z digest=sha256:012c613baf342bb2dc13b60b912a1908aa147d2e97fdbe7385ebe5737fd91af2

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=sha256:263f68a919dc7c765c8684cc0bdf1f64ca44c1a77b2a94242f184b3122cda3d1

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:a1ab972b3546f18428ff8c63a62ce9923eec032b25c2df29435932eb4ed2bece

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.647588Z digest=sha256:c61d47ee57e90e93b1f47440d6491e5f718d2799945cfdee9de7ad4c869a0b1d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.700807Z digest=sha256:2abf10829536212118a5d94c74d79f7360dd55048ad6afceae1df24aa059ad0a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.734235Z digest=sha256:63742f3abb85d892cfc605342d10ec99a35216d52aa6b384a8efe6e2e16b291a

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:fb1b2afa6cc29f2f862697e0a45c46e8005688063100b4f54ac8ef781528b80d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.790451Z digest=sha256:6149a9e5bb38d34924735aa5bbb702c1e73868d90022ac4204b349bcd9400d88

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.805177Z digest=sha256:c52525bb2fe38c06207b9731ef8c07d3d037f457095b18ce5b74d6674ff3a3c7

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:aa8600e08c454724bb8c541a9d39b7e4285de6213f1cfa6a8e196cf5a181f16d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.812114Z digest=sha256:d153821aef31bac8b02bb105ff0cea6b9e6eb6b9cd4ee32dde58a748a1f92a76

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.817008Z digest=sha256:0f2503bba2db28f8c2ecf68e645e77950f5c69cbd69204d82f701342880445fb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:23.822902Z digest=sha256:48d8491449b80af83d859d7640f8ac4c255c57ef1c89b23caecf8a5dccaf525e

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:da064de40e6afbf0aaa91ac6c4973b828205a716162f1efe45535a45ba13d48d

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:c7d788829b97bd9bf355c6a61d11a8f1980c4294d7339bd8c90cb7323601ac9f

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=sha256:1db2ab1a43c7fd5c95c66ebbaf60b88937a30dfd437a1d239d6f52da1385b692

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:24.037222Z digest=sha256:54be3cd169c8a4e457dfb8220778e193c728851ffe30a53cad70d8a2c9d65292

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:24.112267Z digest=sha256:1a61adf355b670bef8529de28a66ecc4eeddff76d1bebd3079c77fc407d2eca7

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=sha256:523eae77792630c50bc0277ba07ddf4c359b73ae9d9674a0415f6a4c581d2fda

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=sha256:1e3f1b74f3a321f11141b8cd86435f05271196e128870faabad9c51fabb46d5d

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=sha256:536646645365641a9d11d4ac5f19e335d5aec827f9ecece5d5c904abafccaa32

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=sha256:3df30aa513cfc6648bee0009cead6ae4e7330eb419ec8a54f4f888ee1eccbfd0

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:ae5b89d87c1336ef6cf1928b160e731f1cf9b2c53081afe316bb5c5ee2935618

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:24.529300Z digest=sha256:1587e72406585624037c4d9850455f520fb692b7849a5bde74010c2b72a5351c

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=sha256:331ed9863f9aa0c7fe54219554dd1146961ba2532df3052e3b9d8ff7d2cfbb7a

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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verified fuzzy
raw_fallback, observed 2026-08-07T14:02:27.757600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:24.606601Z digest=sha256:2b52fdcfd043b9ffeca68ee8c6275d2116d5a86bc46f018f07e82755532d03e1

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=sha256:585cc34277de6456b0234c42c477ee7519c6b36b3e58800203edf7bae72bd714

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:ac963f323e784f085947d3b4a52c0894389a317db2c2507c4d716f876fa05669

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=sha256:46c30a4288d5cc8e1e7e2d5a0ecec9319c125fd1dbebc8ff6ab002a1cbb3a263

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=sha256:0a1a3462eeed0b7027cd031de0e4a81dc33c7336b36a09a260963fe6c9d21e7f

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=sha256:32b88e4b596c5c6eb0e39c2657ae0601d40378b0998fc9c2c6d76badb9a1c969

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

This paper cites Open Thoughts.

Temporal Sampling for Forgotten Reasoning in LLMs Open Thoughts

Reference 43

Resolution
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no resolver link, observed 2026-08-07T14:02:24.795246Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:02:24.795246Z digest=sha256:c6b55455aa89566f578ea5c9ca2e3efd0545354fa18877780d6152e077b0bab4

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-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:02:24.880272Z digest=sha256:1a47a15230e56af51c05c84e2472babc5e49e37dd32cee74079c1b7eaa0fe728

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:24.927393Z digest=sha256:70524e4c2a02a2708628610117d6591b51bf3c7fa6b792ce0c08a5cf9728c820

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:24.991813Z digest=sha256:05377656b8175bd3cc6063e502a29c1b703bc0a6a6e76f0db58c46fd0871396d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:25.038301Z digest=sha256:5b9f114f14654bebeb5f297675b4bc378c989b33cb90ea6b171bb6ee716d00e6

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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no resolver link, observed 2026-08-07T14:02:25.093221Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:02:25.093221Z digest=sha256:93c9ef0f5bddf89806234aa35dd684eb218d2c2d647ba35cdd882ff8bf3471bb

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:e7b6c6cef0598baa6e1321ad58a43c2af2d514e10b837ffada9198161255f210

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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source=pdf_text observed=2026-08-07T14:02:25.245487Z digest=sha256:74adcfc9954ad59c34a854bd031e8498d4be680ae4e12098b2320481f080ee4c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:25.291233Z digest=sha256:20180f21f8b7fbae40d92872b4e5bc1daedcb4017e0daae0b17ef798f806175b

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=sha256:82285ed6e13e00ae761a821ed19a62923afd9c31d75084bb3a10621fc874b3c7

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

Resolution
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source=pdf_text observed=2026-08-07T14:02:25.436004Z digest=sha256:323e65ebcd0681398447ebafbb01fa1baca4dd77b332330d32921db710ff2365

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:ca9dca01e8f15a1e53d9c36770401b60e9a6e3704639711e76c83445f387b3b2

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=sha256:931ca287bf50c95928a53edc9ba4ed42c404d3674e6de33b1b4cf9e22a6afd7b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:25.648741Z digest=sha256:ead0221adcd8a5d8f56f00e350f9d280c775d62d5fe8fb62b35bb935ef605913

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:25.707333Z digest=sha256:ee79cbc4c5f00bec86dbc400340b2946236ff87ac534cf1054a9d8f944319be3

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

Resolution
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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=sha256:21e8c9a2728bb62e9b91ea9703221496595799bca392c7b76a214fd491018c8f

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=sha256:023ffd37edd4a038e7881c97d34b371e3633df4afc3d3070485aee44036b36d8

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=sha256:23e453ea0b6a17e42fd92b56f68b352ecba3607fff571748fe4022efb4fc3213

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:25.976745Z digest=sha256:ebca63f8998bc040a7bfceff804b3f71bf37e047da167344f1364dee3957fa46

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:02:26.048992Z digest=sha256:3d727b579e641bb0884c989419905f0b004866ef809b028bd1951404d1ad23d9

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:d07091f14906715f54177732bdec13d7eff8227239c76b8bba02e4ed3024134e

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=sha256:36dd0282ee3bc4b4407195ca3375ae8f01e869a9ca8f86a84d2502b782201a1a

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

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-18T00:02:24.352947Z digest=sha256:fc3d38e3c73e7c4b16bef0accb58b50f9235242e21091b090447f3d21aa98cc9

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T06:48:28.788806Z digest=sha256:ff79d4f7884012f837e1dfc1f169c5df0452862c3ed3de6cbb1e2e7ecf420b68