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Paper Citation Record · LEDGER

Computational Reasoning of Large Language Models

As of 19 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2504.20771.

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

pith.paper-citation-record.v1
2504.20771 v2

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:24:24.276508Z

measured 79 of 79 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

79 of 79 outbound references displayed

  • verified exact2
  • verified fuzzy15
  • unresolved60
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3db6c078-dce0-42c2-ba65-f4812a0acbfd · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Computational Reasoning of Large Language Models Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 1

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Observation d0bbc28e-e902-4fd7-bcf5-424d34896bc5 · outbound

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

Computational Reasoning of Large Language Models Gpqa: A graduate-level google-proof q&a benchmark

Reference 2

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Observation 8ea08924-f665-4c7f-b542-7d75018331c4 · outbound

This paper cites OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI.

Computational Reasoning of Large Language Models OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI

Reference 3

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Observation 57f84f9d-1233-4249-b249-19b562a30063 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Computational Reasoning of Large Language Models SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 4

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Observation c19e0a54-c25c-49a6-a347-d175c6fed756 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 5

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Observation 141ca28f-a327-43ed-9778-cd426aa09504 · outbound

This paper cites Code Simulation Challenges for Large Language Models.

Computational Reasoning of Large Language Models Code Simulation Challenges for Large Language Models

Reference 6

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Observation d610db86-53cd-48cd-a798-540ba969b815 · outbound

This paper cites NExT-GPT: Any-to-Any Multimodal LLM.

Computational Reasoning of Large Language Models NExT-GPT: Any-to-Any Multimodal LLM

Reference 7

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Observation 7c63d4b5-5046-4999-8eb3-38b3f2af4b69 · outbound

This paper cites Autonomous chemical research with large language models.

Computational Reasoning of Large Language Models Autonomous chemical research with large language models

Reference 8

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Observation 008508a2-4bf5-4e31-bd27-93b7c4a9fde1 · outbound

This paper cites Measuring massive multitask language understanding.

Computational Reasoning of Large Language Models Measuring massive multitask language understanding

Reference 9

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Observation 69e7d8be-71a5-4926-a1bd-67654b118682 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

Computational Reasoning of Large Language Models TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 10

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Observation f2428573-fd22-40b5-b4be-678ee6373d6c · outbound

This paper cites GPT-4 Can't Reason.

Computational Reasoning of Large Language Models GPT-4 Can't Reason

Reference 11

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Observation dfd028dc-986f-460c-a034-26eed404c70d · outbound

This paper cites Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.

Computational Reasoning of Large Language Models Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Reference 12

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Observation 7af7b8ef-8ed3-49b7-a200-d7de92043545 · outbound

This paper cites American invitational mathematics examination - aime.

Computational Reasoning of Large Language Models American invitational mathematics examination - aime

Reference 13

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Observation 0968e1de-fc36-4ace-801e-d7ca73e6da77 · outbound

This paper cites MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics.

Computational Reasoning of Large Language Models MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics

Reference 14

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Observation 8168e342-b4cb-4fde-85c5-0d208ab88d1c · outbound

This paper cites ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics.

Computational Reasoning of Large Language Models ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics

Reference 15

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Observation df63f32a-1318-4e12-a74f-fceca00a9e5c · outbound

This paper cites Executing Arithmetic: Fine-Tuning Large Language Models as Turing Machines.

Computational Reasoning of Large Language Models Executing Arithmetic: Fine-Tuning Large Language Models as Turing Machines

Reference 16

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Observation b9263058-8266-4b4e-914d-a0b8750e40e9 · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4791–4800, 2019.

Computational Reasoning of Large Language Models Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4791–4800, 2019

Reference 17

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Observation 0ce24d1a-970a-41ea-a6bb-6f5aa27cf42e · outbound

This paper cites Holistic Evaluation of Language Models.

Computational Reasoning of Large Language Models Holistic Evaluation of Language Models

Reference 19

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Observation 72835dbc-ee36-4493-b095-d9e9e6bb973f · outbound

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

Computational Reasoning of Large Language Models AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Reference 20

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Observation f8fbd26f-4229-42e4-855e-13f3355c7691 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Computational Reasoning of Large Language Models Evaluating Large Language Models Trained on Code

Reference 21

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Observation 0d98c6df-bb4e-4c3f-bbbf-9bd2312cb5f8 · outbound

This paper cites ToxicChat: Unveiling hidden challenges of toxicity detection in real-world user-AI conversation.

Computational Reasoning of Large Language Models ToxicChat: Unveiling hidden challenges of toxicity detection in real-world user-AI conversation

Reference 22

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Observation a3b3fe43-344a-4018-96a9-f0188ea6045e · outbound

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Computational Reasoning of Large Language Models Unresolved cited work

Reference 23

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Observation ddb7d71c-9505-46cb-bbee-c152c95fa82d · outbound

This paper cites Gonzalez, and Ion Stoica.

Computational Reasoning of Large Language Models Gonzalez, and Ion Stoica

Reference 24

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Observation ddfa2da4-2bde-4c81-a535-be5db0aa3194 · outbound

This paper cites Hashimoto.

Computational Reasoning of Large Language Models Hashimoto

Reference 25

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Observation b041c95b-eeee-4026-82fc-8d978048dd5e · outbound

This paper cites Competition-level code generation with alphacode.

Computational Reasoning of Large Language Models Competition-level code generation with alphacode

Reference 26

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Observation 60c713aa-baef-43bb-99d5-af972c1769c2 · outbound

This paper cites Competition-Level Problems are Effective LLM Evaluators.

Computational Reasoning of Large Language Models Competition-Level Problems are Effective LLM Evaluators

Reference 27

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Observation 4ac22620-077a-4524-929d-8c695c089975 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Computational Reasoning of Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 28

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Observation f835f6b6-1622-49d7-9730-baf42c40272c · outbound

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Computational Reasoning of Large Language Models Unresolved cited work

Reference 29

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Observation f92f8b6e-e031-4894-9a56-958e406caaa3 · outbound

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

Computational Reasoning of Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 30

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Observation 25eda5ea-ed66-4c35-9eb8-f11ec9157c2f · outbound

This paper cites Solving quantitative reasoning problems with language models.

Computational Reasoning of Large Language Models Solving quantitative reasoning problems with language models

Reference 31

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Observation 5bc81cb8-054d-46d2-85e3-0b5d0dc96a78 · outbound

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

Computational Reasoning of Large Language Models Chain-of-thought prompting elicits reasoning in large language models

Reference 32

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Observation b73ec3cf-7691-429a-a4d0-fd0815553446 · outbound

This paper cites Show Your Work: Scratchpads for Intermediate Computation with Language Models.

Computational Reasoning of Large Language Models Show Your Work: Scratchpads for Intermediate Computation with Language Models

Reference 33

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Observation 93d41ad2-bd9e-41ca-8c2c-9b6e60c85b36 · outbound

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

Computational Reasoning of Large Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 34

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Observation b0599313-69bf-4bbf-8d09-7fd17d0d4a2f · outbound

This paper cites Unicorn on rainbow: A universal commonsense reasoning model on a new multitask benchmark.

Computational Reasoning of Large Language Models Unicorn on rainbow: A universal commonsense reasoning model on a new multitask benchmark

Reference 35

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Observation 9e703f82-0379-46be-befa-c1b863d42c53 · outbound

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

Computational Reasoning of Large Language Models Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies

Reference 36

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Observation 9e35e3b2-2dfd-4eea-8f7a-9dc8a475b363 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Computational Reasoning of Large Language Models Training Verifiers to Solve Math Word Problems

Reference 37

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Observation 438f2dd6-5e01-4c05-88bc-d522fbb8d94d · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Computational Reasoning of Large Language Models Measuring Mathematical Problem Solving With the MATH Dataset

Reference 38

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Observation 1e878af2-c98c-4187-abef-4b609cdb1a22 · outbound

This paper cites Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models.

Computational Reasoning of Large Language Models Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models

Reference 39

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Observation 44a4cdb4-c39f-4fe2-afe6-11d21366a1c2 · outbound

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

Computational Reasoning of Large Language Models FOLIO: Natural Language Reasoning with First-Order Logic

Reference 40

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source=pdf_text observed=2026-08-16T05:24:24.108217Z digest=sha256:b830a47842ee9c0bb4d8430cf4cd57da9806ce286cf70e6f9079a44f297ad9a9

Observation 21030ce5-2cc6-421a-bfce-18ab298eb529 · outbound

This paper cites Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models.

Computational Reasoning of Large Language Models Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models

Reference 41

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source=pdf_text observed=2026-08-16T05:24:24.112681Z digest=sha256:3146874eea2f23b79884a298507c0ebdcf523acbb1dc77f63f92ab1fd711172d

Observation 5a67629b-de4b-4984-99ee-a77bf9081f80 · outbound

This paper cites LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models.

Computational Reasoning of Large Language Models LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models

Reference 42

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source=pdf_text observed=2026-08-16T05:24:24.117256Z digest=sha256:fdf638767a96bf206b2e464c5ca4fb0385e7cad7725e34ef5a983009cc243110

Observation 9e96e03c-3d8e-4901-8b37-31ea7de7a7d6 · outbound

This paper cites LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning.

Computational Reasoning of Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 43

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source=pdf_text observed=2026-08-16T05:24:24.121483Z digest=sha256:5217cd984e100dfc1571588bc330e90ff3224cd4fdec55e41ca7dd2ab94dae0a

Observation 65a974d6-3fc2-417a-9274-bc77874eec9c · outbound

This paper cites ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language.

Computational Reasoning of Large Language Models ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language

Reference 44

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no resolver link, observed 2026-08-16T05:24:24.125759Z

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source=pdf_text observed=2026-08-16T05:24:24.125759Z digest=sha256:7ef4201a824d306d93f5b95e255f1dee4e91a0e421c0fc6070c48e31734cdc6c

Observation 4118731a-03fd-4609-a1d2-deb5cda53238 · outbound

This paper cites From recognition to cognition: Visual commonsense reasoning.

Computational Reasoning of Large Language Models From recognition to cognition: Visual commonsense reasoning

Reference 45

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.130187Z digest=sha256:4506811577c7ba6c3f71cdb6ac2bf0089c773d2d988d60e0a40615bbf4acbb30

Observation 1e7a25c8-04d6-47b6-89d4-1b1fe825032d · outbound

This paper cites Next-qa: Next phase of question- answering to explaining temporal actions.

Computational Reasoning of Large Language Models Next-qa: Next phase of question- answering to explaining temporal actions

Reference 46

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no resolver link, observed 2026-08-16T05:24:24.134183Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.134183Z digest=sha256:8433a192c0e5cb37a225eeb88ceec467d7fd3a2359a9914f5550c55b805f62eb

Observation 748c1dfb-19a4-4eff-be5c-ede5af95d6fc · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

Computational Reasoning of Large Language Models Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 47

Resolution
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no resolver link, observed 2026-08-16T05:24:24.138065Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.138065Z digest=sha256:36d859f1618325d4ccd6631859745401de641d304ac5fca0066d2fc6d363c2e3

Observation ad2b1d09-f699-438a-bd8e-921e430017ed · outbound

This paper cites ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints.

Computational Reasoning of Large Language Models ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-16T05:24:24.418464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.142035Z digest=sha256:190311374f5f438b58d9e9aa78380a83c26a4f95bd96b2db0c92fb49a60d9006

Observation 52b8bc4f-de80-4831-9396-738bc8de3dc6 · outbound

This paper cites Axiomatic set theory.

Computational Reasoning of Large Language Models Axiomatic set theory

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:25.099133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.146249Z digest=sha256:93087f981ab710957e0caf33cc22b13c59b8ae39e44eb8cec83bb018bf85f7eb

Observation 5cf32f9d-a120-4cb4-b245-3b25bb9c0ecf · outbound

This paper cites Principles of mathematics.

Computational Reasoning of Large Language Models Principles of mathematics

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:25.085605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.150472Z digest=sha256:41f33cfbf82989eac310399f804b14415a189bcfa92131f841d00a0b616e0c30

Observation a24eb9b7-5aea-4546-ad41-51544772c6e6 · outbound

This paper cites The feynman lectures on physics.

Computational Reasoning of Large Language Models The feynman lectures on physics

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:25.071956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.154695Z digest=sha256:8cfe60a5b1b0cdcca70148df68bb3c7da9243fd80b8179d7a6f9ebe00e84f158

Observation 3e538da2-7a11-4ee6-ae9c-a34a3bb079fb · outbound

This paper cites The game of life.

Computational Reasoning of Large Language Models The game of life

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:25.057146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.158792Z digest=sha256:2459523e1c10b73d5ffb807d9c64ab1604b85b645e47fd80c1cfaf79a373ec7e

Observation 9662313a-132c-4b6c-a86b-66f69ba20c6c · outbound

This paper cites The lean 4 theorem prover and programming language.

Computational Reasoning of Large Language Models The lean 4 theorem prover and programming language

Reference 53

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.162738Z digest=sha256:5f0c2b6fe114472205ea5cdf08ea83392afe603d202d3405ed194997e1754cd9

Observation cddb9a64-7383-4289-893e-e504dc4b334a · outbound

This paper cites On computable numbers, with an application to the entschei- dungsproblem.

Computational Reasoning of Large Language Models On computable numbers, with an application to the entschei- dungsproblem

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:25.035541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.166761Z digest=sha256:bbc079fc112012201af04ec7f142855d64365788ce4b97e397adae625e7683e8

Observation 2af80b93-be6f-4b90-84f8-7862beaf8e01 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:24:25.022090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.171119Z digest=sha256:3de0c1a9d805b8a9d44ad43860d7c59c0c416f25f7546d8d0691f9ef8b2eb13c

Observation 3d232c0b-da39-40c1-b4b7-83aa4488dc0e · outbound

This paper cites Universality of tag systems with p = 2.

Computational Reasoning of Large Language Models Universality of tag systems with p = 2

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:25.009045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.175377Z digest=sha256:66b3c51b0d3c189b5d500a122d9138fc01e5696ada002c2a1135c4d51fc31efe

Observation 3c5f4daf-bc32-4aba-a13e-76111a91f2e8 · outbound

This paper cites Formal reductions of the general combinatorial decision problem.

Computational Reasoning of Large Language Models Formal reductions of the general combinatorial decision problem

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:24.995374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.179495Z digest=sha256:ef58ced6281d6fe09aad3942375b2f1e4dee8d4dae3bcd76b9cd3bf3cd169c14

Observation 227d5f18-6326-4f5b-87b3-09f1b512d2ea · outbound

This paper cites Let's Verify Step by Step.

Computational Reasoning of Large Language Models Let's Verify Step by Step

Reference 58

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unresolved
no resolver link, observed 2026-08-16T05:24:24.183883Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.183883Z digest=sha256:90fb7659b77f9dea503fffd38af04ab909c78218c3dc6bcaad7a7143f2d82853

Observation 0b0e0fda-8985-47c0-9c72-57fd248e86c6 · outbound

This paper cites Mmlu-pro: A more robust and challenging multi-task language understanding benchmark.

Computational Reasoning of Large Language Models Mmlu-pro: A more robust and challenging multi-task language understanding benchmark

Reference 59

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source=pdf_text observed=2026-08-16T05:24:24.188460Z digest=sha256:908f030d36ee53a5eeb0252c4bee65299c633432da6e8d7cae6bb6bf46464dce

Observation bc814878-8adf-43e5-97ef-bd22a23dc4d1 · outbound

This paper cites The Llama 3 Herd of Models.

Computational Reasoning of Large Language Models The Llama 3 Herd of Models

Reference 60

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source=pdf_text observed=2026-08-16T05:24:24.192514Z digest=sha256:0ca9aba739a4030af6e287693b2f9a330c61bf10cb6a5087e7a7eb553eb22c9d

Observation 741b2e20-46bc-4ebd-8437-496385069bb0 · outbound

This paper cites Qwen2.5 Technical Report.

Computational Reasoning of Large Language Models Qwen2.5 Technical Report

Reference 61

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source=pdf_text observed=2026-08-16T05:24:24.196881Z digest=sha256:2bdbc5f25b3aba71104c16459a20201bc3d36f11d7281107b1ee6d3aa9d6dd88

Observation 95d1352e-653f-45ce-8449-b75532c886ce · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Computational Reasoning of Large Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 62

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source=pdf_text observed=2026-08-16T05:24:24.201184Z digest=sha256:84b78b65dc84930b32a50a61726f9c350c930c9908be67b457f4bc851d438e95

Observation 4bb87cb8-6a67-4f4a-917d-9afa40479f92 · outbound

This paper cites Qvq: To see the world with wisdom, December 2024.

Computational Reasoning of Large Language Models Qvq: To see the world with wisdom, December 2024

Reference 63

Resolution
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no resolver link, observed 2026-08-16T05:24:24.205393Z

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source=pdf_text observed=2026-08-16T05:24:24.205393Z digest=sha256:af05352c44740eea20c7f0157c66f4b324178d54373e8224ea1e92455ed7fe50

Observation e3ba6691-c3f5-4467-8849-fed18d4638e0 · outbound

This paper cites Gemma 3 Technical Report.

Computational Reasoning of Large Language Models Gemma 3 Technical Report

Reference 64

Resolution
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source=pdf_text observed=2026-08-16T05:24:24.209191Z digest=sha256:f9901a1eb77c89f4b94ba62e8d79e1fb61f82eaf7ff5008d04fc803fea25c81d

Observation e44ab2b8-0002-45aa-a210-c81cc21e9f07 · outbound

This paper cites Sky-t1: Train your own o1 preview model within $450.

Computational Reasoning of Large Language Models Sky-t1: Train your own o1 preview model within $450

Reference 65

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raw_fallback, observed 2026-08-16T05:24:24.963860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.213459Z digest=sha256:c5ae7847904617408c55abb6c097ebb2bd68d2b90d463c5fce66d11a68fe0c67

Observation 8ed19abe-d9ca-4b92-bebc-87cebc911ecb · outbound

This paper cites Gemini 2.5 pro, 2025.

Computational Reasoning of Large Language Models Gemini 2.5 pro, 2025

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:24.949008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.217596Z digest=sha256:803c477d302c9eedd5077dd496f8af2d0d984b960ed167870c7c5b58a7a4ca6e

Observation 473b500a-e1e4-4672-80a3-5e3f981c6f00 · outbound

This paper cites Grok-3, 2025.

Computational Reasoning of Large Language Models Grok-3, 2025

Reference 67

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raw_fallback, observed 2026-08-16T05:24:24.935020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.221556Z digest=sha256:7dd3edbba3ca8a2507816943d4ec4a82bc1f3c2a595d7fe910cc3887371ffc5a

Observation 0e56f3bc-62e1-456a-8d02-c90896a9e67d · outbound

This paper cites Claude 3.7 sonnet thinking, 2025.

Computational Reasoning of Large Language Models Claude 3.7 sonnet thinking, 2025

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:24.920671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.225579Z digest=sha256:ba366ad2bd60a5605215e8f20afd1bc6d7ec3867e3b10908510cd68972b19ca2

Observation a1b1f9ba-dfed-4ac8-8038-99cdff12c5bd · outbound

This paper cites Doubao 1.5 pro, 2025.

Computational Reasoning of Large Language Models Doubao 1.5 pro, 2025

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:24.906562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.229764Z digest=sha256:652df35bce04b989301ca4f13d5bd3318cd025948c0fadf24f255460d982a958

Observation 00372d6b-5b30-43a3-8df7-53fa95a942ae · outbound

This paper cites Openai o1 system card, Sep.

Computational Reasoning of Large Language Models Openai o1 system card, Sep

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:24:24.892734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.233656Z digest=sha256:4041fa6f739957e9edbcafe045d66723e4f5e865ba8de3655d476cd873335c41

Observation d550bf3d-3e79-49a1-a2cc-b02c2ff21db7 · outbound

This paper cites Transformers: State- of-the-art natural language processing.

Computational Reasoning of Large Language Models Transformers: State- of-the-art natural language processing

Reference 71

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no resolver link, observed 2026-08-16T05:24:24.237386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.237386Z digest=sha256:1e8d3b92c9653c337d5a5941ea2c15e96e21656526bdd593edba9ea9460b50f2

Observation a00b2724-f417-45a8-b23d-80344401f383 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Computational Reasoning of Large Language Models Gonzalez, Hao Zhang, and Ion Stoica

Reference 72

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.241422Z digest=sha256:5b7260b1afbdc5d22ba21a206814dff8b4a6e1a4dcb1661db07dffe31affed75

Observation 2cb08eac-a922-4a33-894a-e8f266ac8fc6 · outbound

This paper cites Emergent Abilities of Large Language Models.

Computational Reasoning of Large Language Models Emergent Abilities of Large Language Models

Reference 73

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.245638Z digest=sha256:52fdb6464760bfb3f7f7535b63b6caca23d0be756ef9da68ab68fcef80f52990

Observation a757518a-1f11-4db0-a5c3-de265cc0ce88 · outbound

This paper cites s1: Simple test-time scaling.

Computational Reasoning of Large Language Models s1: Simple test-time scaling

Reference 74

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unresolved
no resolver link, observed 2026-08-16T05:24:24.250074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.250074Z digest=sha256:179b594e6e5995e955c58b4d9afdb1aba5d708687d17f1232fb3c32b49b8ddb0

Observation 82b116c5-0a04-4d18-b3a2-2b68e31ac268 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 75

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:24:24.860691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.254417Z digest=sha256:55e6e25445bbb05664ad7b3a29636667ed68ff932c3aea3e363634c5c94cd87b

Observation f0778518-0310-42a1-a0de-a5735a80e048 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 76

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:24:24.846062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.258815Z digest=sha256:8167cf82de43603178792ee7bf4024de423c3f2b7c91a39bb41483dae5bb2c93

Observation ed0085b0-a9f5-47d0-a735-76b78afbf756 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:24:24.831941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.263118Z digest=sha256:61fb1f065fc2b22d7d68b16311905ebffafc5ac090c3547f7e9ce063009dc267

Observation 8972f39f-8816-44b9-ab7c-acedc965c993 · outbound

This paper cites • If S′ = 1, the next state isQi1.

Computational Reasoning of Large Language Models • If S′ = 1, the next state isQi1

Reference 78

Resolution
malformed identifier
raw_fallback, observed 2026-08-16T05:24:24.818121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.267897Z digest=sha256:bef7095cf4789781f077d44cd3a14d3c840ad037ab1d6289177eae60981b3666

Observation e0e0ea02-38c7-4b63-aef9-eab2bdcd0ac5 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 79

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unresolved
raw_fallback, observed 2026-08-16T05:24:24.804132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.272331Z digest=sha256:6b521e1a8beca27ff884c57fd3fdf397090b55994340e2ebddde9144e2cc5627

Observation 7b693ade-79ba-458c-819e-9fa314edcf31 · outbound

This paper cites an unresolved cited work.

Computational Reasoning of Large Language Models Unresolved cited work

Reference 80

Resolution
malformed identifier
raw_fallback, observed 2026-08-16T05:24:24.789904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:24:24.276508Z digest=sha256:375c80c8d7830eacd75562f3417e8068c9720f89c1a378f1f489b01cd61c6d14

Pith citing papers

No inbound Pith citation observations are available.