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Paper Citation Record · LEDGER

Pheromone-based Learning of Optimal Reasoning Paths

As of 17 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2501.19278.

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

pith.paper-citation-record.v1
2501.19278 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:47:53.741226Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

50 of 50 outbound references displayed

  • verified exact6
  • verified fuzzy9
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 876c11e9-014c-4304-8c76-5b2e5841d78e · outbound

This paper cites Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation.

Pheromone-based Learning of Optimal Reasoning Paths Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation

Reference 1

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source=arxiv_source observed=2026-08-09T20:47:53.540332Z digest=sha256:62b99e473fe79bd07832ea03a07b67fb17a2beda090d643ae3d77b193e9438cb

Observation 71afa37a-a4fe-4b31-a06a-f27dfdfd6f91 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Pheromone-based Learning of Optimal Reasoning Paths Constitutional AI: Harmlessness from AI Feedback

Reference 2

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source=arxiv_source observed=2026-08-09T20:47:53.545755Z digest=sha256:e47c76e6b696e09d2ed46c37bf31c640e677583fa9b0a8aa35974e6e62dc2d1c

Observation 07cf43b2-d80d-4545-9adc-1e6f938570cd · outbound

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

Pheromone-based Learning of Optimal Reasoning Paths Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Reference 3

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source=arxiv_source observed=2026-08-09T20:47:53.550748Z digest=sha256:5375fc936ab8ded17810c3cce4d3b65e6da24de5d4121223538d2c38d9c7adde

Observation 7db47897-5a70-46eb-b456-40a9ec713896 · outbound

This paper cites Ant colony optimization: Introduction and recent trends.

Pheromone-based Learning of Optimal Reasoning Paths Ant colony optimization: Introduction and recent trends

Reference 4

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verified exact
doi, observed 2026-08-09T20:47:53.801112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.555241Z digest=sha256:ef3073623fcec9cdbcc14e219cfc617a32e6d6b9c5eeac1634acd9324acf938c

Observation a6af65c0-41c6-44b6-819b-229f7e651b79 · outbound

This paper cites Language Models are Few-Shot Learners.

Pheromone-based Learning of Optimal Reasoning Paths Language Models are Few-Shot Learners

Reference 5

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source=arxiv_source observed=2026-08-09T20:47:53.559650Z digest=sha256:7af2b0e105bfdb309b296ec32ed5c3507f5e1953552359945e389de869570913

Observation 14a3eb59-1043-487a-a3f3-5652f7c76f66 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

Pheromone-based Learning of Optimal Reasoning Paths PaLM: Scaling Language Modeling with Pathways

Reference 6

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source=arxiv_source observed=2026-08-09T20:47:53.564628Z digest=sha256:74eea40dbe8e9f29be279db564b8a70821d8bf4339ee221e87398fe6be67ead9

Observation 79fb3571-47d9-463d-9193-eca1e6cec20d · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Pheromone-based Learning of Optimal Reasoning Paths Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

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source=arxiv_source observed=2026-08-09T20:47:53.570005Z digest=sha256:bba75a9a80dcd0c421b221f9813e3c65a5fa14171b47128249fc38c0ef450da7

Observation f7ed84b6-3f20-4d50-8ffb-3036fba50501 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Pheromone-based Learning of Optimal Reasoning Paths Training Verifiers to Solve Math Word Problems

Reference 8

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source=arxiv_source observed=2026-08-09T20:47:53.574726Z digest=sha256:8ea6b064ca7113116bc5a3ff9a744863d3eab5d256873c580825881af47cce53

Observation de0eced6-2ae1-4e33-960c-c46f45a887a6 · outbound

This paper cites Active Prompting with Chain-of-Thought for Large Language Models.

Pheromone-based Learning of Optimal Reasoning Paths Active Prompting with Chain-of-Thought for Large Language Models

Reference 9

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source=arxiv_source observed=2026-08-09T20:47:53.580078Z digest=sha256:6443d330c9c975cdc3541367ea6f522323c95550919310f6495c07186f158095

Observation 9536f507-de8c-4024-9bfe-60e4fa5f3766 · outbound

This paper cites and Di Caro, G.

Pheromone-based Learning of Optimal Reasoning Paths and Di Caro, G

Reference 10

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arxiv_id_nonexistent, observed 2026-08-09T20:47:54.349834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.584478Z digest=sha256:0d80c99dc5818c0d291b53cf78e3792f6ecb62fdde691ac064251fa510a11e58

Observation 7745fde7-e0ee-452b-b829-43644d3d1e69 · outbound

This paper cites and Stützle, T.

Pheromone-based Learning of Optimal Reasoning Paths and Stützle, T

Reference 11

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source=arxiv_source observed=2026-08-09T20:47:53.588634Z digest=sha256:e6dc37d5091288b016c3f50108bd55e6349ba4efa25d753fc706d633804e652f

Observation 06e114f5-e276-43e2-827d-c6749236b28a · outbound

This paper cites Ant colony optimization.

Pheromone-based Learning of Optimal Reasoning Paths Ant colony optimization

Reference 12

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.593042Z digest=sha256:1002c4237decc6c1d717abd31327dd83d5966c15ea7ae8d2a3e501f3c3779441

Observation 63562dbf-31b1-4a9a-b87d-a41d36aff6d0 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 13

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.596875Z digest=sha256:3696af51485c536a77f6c86dcd50c21f04da2fe6223efdd31f7448d7fd7a79d1

Observation 9b30afa3-5ffb-44d9-9f48-637e4b2d8d0b · outbound

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

Pheromone-based Learning of Optimal Reasoning Paths Measuring Mathematical Problem Solving With the MATH Dataset

Reference 14

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Observation 81ccc663-293d-438d-afd6-f3be76756b96 · outbound

This paper cites Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents.

Pheromone-based Learning of Optimal Reasoning Paths Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Reference 15

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source=arxiv_source observed=2026-08-09T20:47:53.605433Z digest=sha256:a655d0cf880e8e511a1c208b38ed4376137d20de27d20a78eb0a4709d444822a

Observation db712744-d184-4ebd-8c2e-ca61b3d386dc · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

Pheromone-based Learning of Optimal Reasoning Paths Large Language Models are Zero-Shot Reasoners

Reference 16

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source=arxiv_source observed=2026-08-09T20:47:53.609655Z digest=sha256:4cb97e6993b6e9a4b3002ccee47c19ae57871c8f7d724f879c98e001be8bc874

Observation 6e89cde2-786d-4c15-be74-287631049230 · outbound

This paper cites Neural Architecture Search using Particle Swarm and Ant Colony Optimization.

Pheromone-based Learning of Optimal Reasoning Paths Neural Architecture Search using Particle Swarm and Ant Colony Optimization

Reference 17

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local_arxiv, observed 2026-08-09T20:47:53.942390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.613687Z digest=sha256:b0f265d78d1a82a4c8b4a519386bfcab5e92da3800f607a06834be4528592a84

Observation 36e99880-3e2c-4a38-b435-49a96baa208a · outbound

This paper cites Guiding Large Language Models via Directional Stimulus Prompting.

Pheromone-based Learning of Optimal Reasoning Paths Guiding Large Language Models via Directional Stimulus Prompting

Reference 18

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source=arxiv_source observed=2026-08-09T20:47:53.617647Z digest=sha256:9d6c6a110b2c1a0ade7d2b10b34d8ec116046d533fdbe084e1d252f98010a70c

Observation a36ba740-5bcb-41b9-b550-17b9d625bc05 · outbound

This paper cites Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems.

Pheromone-based Learning of Optimal Reasoning Paths Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Reference 19

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Observation 366b3cde-5d3e-4a95-9f19-67f8600e82d4 · outbound

This paper cites Faithful Chain-of-Thought Reasoning.

Pheromone-based Learning of Optimal Reasoning Paths Faithful Chain-of-Thought Reasoning

Reference 20

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Observation 03a455e0-f8be-466b-96d4-cbb5ef7b7ec1 · outbound

This paper cites and Singer, W.

Pheromone-based Learning of Optimal Reasoning Paths and Singer, W

Reference 21

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doi, observed 2026-08-09T20:47:53.781966Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 42954265-fb03-41fe-9efd-1ae31c5d4308 · outbound

This paper cites and Simon, H.

Pheromone-based Learning of Optimal Reasoning Paths and Simon, H

Reference 22

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raw_fallback, observed 2026-08-09T20:47:54.636384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.634082Z digest=sha256:e000932153d60f920cb8aa0f95b588197894039b7d8ac333ae79d0a0b54b440d

Observation 1892e685-8d29-476f-b20b-3d3bb3afe9ca · outbound

This paper cites Getting MoRE out of Mixture of Language Model Reasoning Experts.

Pheromone-based Learning of Optimal Reasoning Paths Getting MoRE out of Mixture of Language Model Reasoning Experts

Reference 23

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source=arxiv_source observed=2026-08-09T20:47:53.637760Z digest=sha256:b24b1d74bbc426d8adffcadaf2b97305cdc2592532a043937326788bfa57cc16

Observation c7b837cc-71e0-459f-8e1a-cf4f99f6ae51 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Pheromone-based Learning of Optimal Reasoning Paths Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 24

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source=arxiv_source observed=2026-08-09T20:47:53.641484Z digest=sha256:d74d9a25f8655c6a6cfbdeef60b5f49edf211b75e3441c4c057aa13b2ecb3b82

Observation b90e57d1-b16c-4747-8d01-10f0f3d67584 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Pheromone-based Learning of Optimal Reasoning Paths Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 25

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source=arxiv_source observed=2026-08-09T20:47:53.645184Z digest=sha256:a59a0e06b8c54a49a48287cc1972b2f8eb76358e1d1e45937b3cb82a8e7c239e

Observation 4461920d-e2f1-4c79-9b8f-75566218706d · outbound

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

Pheromone-based Learning of Optimal Reasoning Paths Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 26

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source=arxiv_source observed=2026-08-09T20:47:53.649083Z digest=sha256:2bceb5cf3e38722e0e9ae0ea4e70f4256cf5453833cdc5fee1102ee015298d85

Observation 80142681-f421-4fb3-b10b-9e7c328d1250 · outbound

This paper cites DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization.

Pheromone-based Learning of Optimal Reasoning Paths DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

Reference 27

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local_arxiv, observed 2026-08-09T20:47:53.866490Z

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source=arxiv_source observed=2026-08-09T20:47:53.653157Z digest=sha256:8e89c7cb06e5681a6d59ddaeeea4436fa9bd8ba530232bd73c4354b6de98e900

Observation 85fdba8a-1974-4145-8b1a-fe3bd2773aba · outbound

This paper cites STaR: Bootstrapping Reasoning With Reasoning.

Pheromone-based Learning of Optimal Reasoning Paths STaR: Bootstrapping Reasoning With Reasoning

Reference 28

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source=arxiv_source observed=2026-08-09T20:47:53.657069Z digest=sha256:e2bca03226d08920f8e6d9665b012e46849363c7ba006365bdee86b92a125965

Observation 4a46916b-0bfd-466a-9b18-cced90b8dbcd · outbound

This paper cites Cumulative Reasoning with Large Language Models.

Pheromone-based Learning of Optimal Reasoning Paths Cumulative Reasoning with Large Language Models

Reference 29

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source=arxiv_source observed=2026-08-09T20:47:53.661161Z digest=sha256:8e95f969c208d9c081bfdb60820b1a280d9b91b359ec78bbb6a1ffb07884a73d

Observation 7bc6c0c7-3a97-4e33-82ce-529ce1e934be · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Pheromone-based Learning of Optimal Reasoning Paths Automatic Chain of Thought Prompting in Large Language Models

Reference 30

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source=arxiv_source observed=2026-08-09T20:47:53.665075Z digest=sha256:af2dcaaa713e194c32565c37c3b4b5fe8c3187fda954185e33b4641bff0d315c

Observation 181ae288-2141-4bb4-823a-d26ebf013f3a · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Pheromone-based Learning of Optimal Reasoning Paths Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 31

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source=arxiv_source observed=2026-08-09T20:47:53.668863Z digest=sha256:c905115656ec4bb2fc78158baa102280eda8b4afef25787aab5af98f75e640c0

Observation cead6494-cfa7-4513-bb88-5d1593579148 · outbound

This paper cites OLMoE: Open Mixture-of-Experts Language Models.

Pheromone-based Learning of Optimal Reasoning Paths OLMoE: Open Mixture-of-Experts Language Models

Reference 32

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source=arxiv_source observed=2026-08-09T20:47:53.672670Z digest=sha256:81913575eb7a7e21da97abe9a31c013b0dc5932e49eebf143185dbd8b7291609

Observation 0c762da3-0370-464b-84fd-cb59ecaa6632 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 33

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation bbf1ae04-738f-4d12-abf2-b42e450300f8 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 34

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 627bfd79-b62e-43c6-8428-6f17fa021086 · outbound

This paper cites GLaM: Efficient scaling of language.

Pheromone-based Learning of Optimal Reasoning Paths GLaM: Efficient scaling of language

Reference 35

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b543c52c-ac42-453b-80d4-833791f80e16 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 36

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Observation be006feb-ab98-4631-b249-ac31bb881b16 · outbound

This paper cites S., Reid, M., Matsuo, Y., and.

Pheromone-based Learning of Optimal Reasoning Paths S., Reid, M., Matsuo, Y., and

Reference 37

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.692232Z digest=sha256:8ebe696aab53040095ce7e95a6f7cff004d82a96c29437abbf70d375f9e65b93

Observation 49fc8a55-fdfa-49a2-a5a8-de2a9600eb87 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:47:54.573822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f6903114-65df-4178-b7ad-3532c4ae736c · outbound

This paper cites Faithful chain-of-thought.

Pheromone-based Learning of Optimal Reasoning Paths Faithful chain-of-thought

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:47:54.563808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.699977Z digest=sha256:964391582ddaa11af0bb1ecd03fbbff03ea5239a2c1bd00dc390585a49630c3a

Observation 85a383f6-bd29-422b-8435-665ac3f1173e · outbound

This paper cites Outrageously large.

Pheromone-based Learning of Optimal Reasoning Paths Outrageously large

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:47:54.552859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 41469588-7174-4333-86d4-88919e4aa119 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:47:54.541700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.707402Z digest=sha256:95f8712752a385c6cd9b37505986b80f867d9f0e6cb6f6f3c9a554f08bf27358

Observation 27365a93-de13-430a-b93c-a6996adbab55 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:47:54.530252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.711153Z digest=sha256:bca73e77e1419ce69b6a092e852cbbe798d6a362f21c715324517185598b0cd6

Observation 45612b6a-e317-4ae0-8746-130d9a42773f · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:47:54.519422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.715437Z digest=sha256:0798d7e15171636b0bfdaa9a974a60694eb4dbe0759edf1cd217f135a6f331c8

Observation 6e69dcf2-59b7-453c-bd9c-f90c46fcdc05 · outbound

This paper cites DeepACO:.

Pheromone-based Learning of Optimal Reasoning Paths DeepACO:

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:47:54.508065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.719308Z digest=sha256:97c9b8dc35d8168164a76e0b48df4d6dfd9675b16ec682554f676875bee4843b

Observation 89973671-d6e3-447a-a21b-126f826847c4 · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:47:54.496632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.722879Z digest=sha256:23312baacb481958acd942bf7ad7808092293af6d9a9841fc465a8e75a270a11

Observation fd513926-0138-49f4-954f-e407fcc0211e · outbound

This paper cites an unresolved cited work.

Pheromone-based Learning of Optimal Reasoning Paths Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-09T20:47:54.485683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.726280Z digest=sha256:97e30c1b90e23c85e4a28745004d5d15274b316183ccfd1f45c0763e6d249096

Observation 8e2201fb-6fd1-48ac-8105-57b9c9a310a5 · outbound

This paper cites Cumulative reasoning with.

Pheromone-based Learning of Optimal Reasoning Paths Cumulative reasoning with

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:47:54.474935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.729889Z digest=sha256:534b629907e65e7cf2db4ec1267b1f5a78e1bb3fbc15e712ee84efadfee42d8a

Observation 8c73b51e-39b9-4db9-916f-2abaf3f2262f · outbound

This paper cites Neural architecture search with.

Pheromone-based Learning of Optimal Reasoning Paths Neural architecture search with

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:47:54.464036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.733476Z digest=sha256:ed6523a8d7813322cdccf0b4cbb03838fef200f4e49721140d502e3d54cde169

Observation 8ece30d5-b866-41a9-a11c-8234b41a68e3 · outbound

This paper cites Weng earns \ 12 an hour for babysitting. Yesterday, she just did 50 minutes of babysitting. How much did she earn?.

Pheromone-based Learning of Optimal Reasoning Paths Weng earns \ 12 an hour for babysitting. Yesterday, she just did 50 minutes of babysitting. How much did she earn?

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T20:47:54.452151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.736977Z digest=sha256:0ede2a6464e0e3dc96463f8ad7f6dd0e87d34d887dd7ae7685ef66097da64a92

Observation eb67fed2-36fc-418d-9735-7d0665136223 · outbound

This paper cites write newline.

Pheromone-based Learning of Optimal Reasoning Paths write newline

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-09T20:47:53.741226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:47:53.741226Z digest=sha256:cd6e04c6520ca3234f57cd86bf0c1a1aad886cf7d8b43680fc649ab154473adb

Pith citing papers

No inbound Pith citation observations are available.