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Paper Citation Record · LEDGER

Computational Reasoning of Large Language Models

As of 17 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 2026-08-17T06:30:58.91139+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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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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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

This paper cites an unresolved cited work.

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

This paper cites an unresolved cited work.

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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source=pdf_text observed=2026-08-16T05:24:24.099211Z digest=sha256:c399a2de578446369dde0351de094461602e6aa246bd9fd63b5cd53b745c3dd2

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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source=pdf_text observed=2026-08-16T05:24:24.103718Z digest=sha256:5c9045821c0dbd9c8e15a4db5db4f77dc5b5dc530f1519625679e8866a4f22bc

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:dbdfe3a14e8e83f2f4b7608fc5c2ccb75147dca466697ce62b7c5baeeda27cf8

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:d4c2d36286607f2f1e072b91a8fbb4b43f553b1838b7e2bcebfca9fe5de6e39a

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=sha256:2403db03646a557583ffee616124116d57dc6954bfe9fddd03f477617e11ea2d

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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no resolver link, observed 2026-08-16T05:24:24.121483Z

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source=pdf_text observed=2026-08-16T05:24:24.121483Z digest=sha256:1674a3340bc8560bde898f1e59faae67b908e0431123d90e86b6395b8a123ff8

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=sha256:64ddeaa8800e9684607145a13c415ce6bb5178bb7815f812cd71109af4ab059c

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

Resolution
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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=sha256:31074dbf1504cb400e799c0a2454d0aea5c19d1e07d087689a24de0a58faea21

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.134183Z digest=sha256:f921ef1b2bddfadf06ead2bc3d906ba866b8ec1dc143fcbacd2cc6cf4456e2f9

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

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source=pdf_text observed=2026-08-16T05:24:24.138065Z digest=sha256:13d7cdc959d47f058c4eef3baa790a326b5498480d406d87225ab12d476b9413

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.142035Z digest=sha256:5e2022f4af1e90d24547952b00479f899e94e93153e0b5194cf19407acc76b0c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.146249Z digest=sha256:59fbcaf9633cec15c23e26f12370e878ef3078c2f46a93ffc71066785b8c207f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.150472Z digest=sha256:89f27aa9a4c4d75aeab566b60dae5430eaa72327761e9f626226cb4a2629dcd2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.154695Z digest=sha256:278b896c9f40491eb3ac0331bdf76c78c0f72d71d1fbc5a5c3ae21fc6ca7ab3a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.158792Z digest=sha256:828d6d0046d7de2f05cbfaf75539faead412562d68701c7047c2ec3b713d9bd7

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=sha256:0d8b3a7ae4b64aaa82a85ab79d94e220382d0f2fb79055f4ef44a20c2ccc71cf

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.166761Z digest=sha256:9ce5d3c6771e6838d55dcb8688f93e1d2dd8894cfcc59ce58d535730555eecfe

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.171119Z digest=sha256:ec9d9fb43e98ba6aea4cf761e4e991554e3e934297362ccdbe004eead88079af

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.175377Z digest=sha256:542f70c535c43c031fd435422ea49c891d42719e0600066bb1cd1869c6264ab0

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.179495Z digest=sha256:cc70fe400d42aa7553cbef3bfb457693e082043927dd6cb0ed87ac490da820d9

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.183883Z digest=sha256:2aac28d7a80fed829529ca4db2337821d3e10ca7fd303d323964543a5b3b473d

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:fbb275411a041c72bae8168567f6cf19299f36e9dc8c0116d0c517a7f7fe4e94

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:aedf3ac2347a357dbd3f37e5f00b5165414e174350e8fadedba4fc1dc18949bd

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-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.196881Z digest=sha256:74634e6efed53f1f209534187375f2b32e5aa1d3ae19b067131732f91a56156d

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

Resolution
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no resolver link, observed 2026-08-16T05:24:24.201184Z

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source=pdf_text observed=2026-08-16T05:24:24.201184Z digest=sha256:68e4960c917c545ff0167086db69870c889c76e62058f387a3de165bcf2bec21

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

Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.205393Z digest=sha256:7a29aad3a19c3c4ee86d1018fad7cf54866db1e9d8a30639cb98dd73bdcef13e

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-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:24:24.209191Z digest=sha256:c24059d2162d910cd0616b2a74f32dc6790516c64dbd2c2f20ebbcf3e926dc67

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

Resolution
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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.213459Z digest=sha256:563d4986ca8d477ee2fbdbbf35405e32d0fb4b8b92968a031c2126d0ccf93fc1

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.217596Z digest=sha256:628ba8b777d6586f6832a4d2ebb35d26ba5959254ab30f6c5638e9da50fbbbb0

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

This paper cites Grok-3, 2025.

Computational Reasoning of Large Language Models Grok-3, 2025

Reference 67

Resolution
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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.221556Z digest=sha256:6004b94de548e568f435f587acb26afff774d9e6bdd81bcf687f00bde05f262f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.225579Z digest=sha256:48e931f0fdbd9819be5cdc4496550d9370000dbd0f675d5da4cfb0474b40d472

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.229764Z digest=sha256:08441bf16d441fe1ccb8a6cf6e4cbca15b8efdd93c50f1bc32eceff0737aa333

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.233656Z digest=sha256:5154b9f3a353ff80a6c53f04d3cb14dd639d2bd483f4d18a815042cd50da491a

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

Resolution
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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=sha256:907a4a5199fb17442ea7a6cc227057c941df38b0c49d8015cd068a77685539a0

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:de613332291ddf796acb95c79f29ff62aa8c3f11b4befa9491b9cfdf10d28ce4

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.245638Z digest=sha256:1c196f2ebf7da3643d3f5080956e0dc05edfbc75a2836550bb25d29bb233d9c5

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:24:24.250074Z digest=sha256:1f4f9fe67266c97ba08712df29571eb7c2c5fa320c0613c0fe75a667fff31c16

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.254417Z digest=sha256:119c666921af6ef7ead80482a80402f2f7e9fa5cc018572c0935d69e19ec213a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.258815Z digest=sha256:010cd2e1cc5680086b25a7b85caf606f7af193bbc765f0a894452fd426a65fa4

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.263118Z digest=sha256:3fbf99de753f970b4b0c3236255cb9a3e2f782615790279061d0ba045b69efa1

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.267897Z digest=sha256:97bc949bb9885a749a14634b0a7edddbe1c6e3555b3d139da2dd237ed061df9e

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

Resolution
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.272331Z digest=sha256:fcb05879dc8e2b2316d56df2a27ba270e466a232eb89be3cc4a9a55e8ba661ae

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T05:24:24.276508Z digest=sha256:22d3a2d60976995805588a62776c6cf9e8928659069e30ef0417adb5290b686c

Pith citing papers

No inbound Pith citation observations are available.