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Paper Citation Record · LEDGER

Pheromone-based Learning of Optimal Reasoning Paths

As of 10 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 2026-08-09T06:31:02.800959+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:a5918bcb32f4dd3c8f134352f847534d257a740eeaf57c891470c7b12737685e

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:fd2ff8d887ea35ae9c52efa434440c0b5dc283b53cde4b8df49a62e721ae044d

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=sha256:770f19936ffb0e436edf520bd5055e8e4efc1d1d5addd332fc2655bee96f438c

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.555241Z digest=sha256:346e13ab4a93b41594835d7b2661c7950984f76143cd3cb5aec7d72203881270

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=sha256:6934653170bb66556fa4236f0738b5a1cc4da23f35fd174319b2fa6b03de7864

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=sha256:0075a2ba17a2a594748cc8d69c3a564133297260bd3ed3be6f48c0b8ebfd32c4

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=sha256:3d845c48b419402bd5008bccf4f6b21ea39abe7ef53aeb12f46da9d6406ad7d8

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:cf340a19d1a66026746d49940aed51b01ca921d3184b6d7322ea3f10e9e0081f

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=sha256:305d87aebf7d6406d88fcd1fd39815dbf5c04aed0bb2f710a3016a9aa2c84f9a

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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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T20:47:53.584478Z digest=sha256:5e7b96678c3cf30e0cbf104d741fab89a98d868cbf2886fdc62a15a867b7640e

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=sha256:1b7a0c2c95e5447578d23fc2230b0c882f8fee1392e3a10a9a70997738541579

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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arxiv_id_nonexistent, observed 2026-08-09T20:47:54.182254Z

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

source=arxiv_source observed=2026-08-09T20:47:53.593042Z digest=sha256:8fe66efc1d69a00a52fef0baeb17794eed37ca9aab621e2bd739cc8e7372f0db

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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source=arxiv_source observed=2026-08-09T20:47:53.596875Z digest=sha256:8571c2a08e5df15a4073085039ad1262cbadf42c64fd488f9dca814d8b2dbe38

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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source=arxiv_source observed=2026-08-09T20:47:53.600986Z digest=sha256:c0b200933541a1cd8e4183c56ceedc8bc46ecf8ec2c1f35a24911c35ecb57808

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:dfff9d10e130bba86242e65ac8bba75f559724fe44a0527a8509781ed6ce43a4

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:ad674fa056ba01ba8a3ea37b9b0b783d453046e397fb09b9d6fa0365c825e8b4

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.613687Z digest=sha256:134f41cd89775ffa39c52082ca24ae36e88b29c5d196cb3232124223f2d18f72

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=sha256:1decb93342d4b695db25addd37b1558d952e8f1d31f2fcdc3dc2796e2d337d04

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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source=arxiv_source observed=2026-08-09T20:47:53.621968Z digest=sha256:86ec0f4f5c72fd9bc472c96f5bf7ec1f011f31495d5407bf4f17e449ef8b1725

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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source=arxiv_source observed=2026-08-09T20:47:53.626096Z digest=sha256:659ba8a283328de5cb4e1b04c0598a786087a7a4c948aaf75eb381194c4fadf3

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

Source-reported events for the cited work

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

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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

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

source=arxiv_source observed=2026-08-09T20:47:53.634082Z digest=sha256:d5a5eb9af7894ab4a0f2692baeca7d18b29a07d1d5f153e8bba760f11ce47561

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=sha256:7981208c24a912267870b5bb11619f79d30298a0315d4588731ded655daa5160

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=sha256:7c99da9846fbea80e1cd466110662bb5d01f4d01ee98e9fa53568722782901a5

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:b437502780b4f6eecc1f4361f9de03038b29d34736230ad1f5a7d8996f5f33f7

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=sha256:224e2c2fd839bf4e77febe8b0ab90c84865c0de04d914c4cb62eb787f72d5c4a

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:d60f592a9636b7915c3e63a50b5588e3d01b650a0b610c73353f3000c0e2fbfc

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=sha256:7749b53096ef751d931009e018fc837f74892a847cd09cd11f1d326fbbe6c4b5

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=sha256:9b34e3f9ba46b81c284ce3e3d2f0fbec189359cce5e6e9ba0a83beb869f19c66

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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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:e6b4d843251a2a29fbc10a9496b3c50e1eef659fd8ec14ed7ae983623df8267b

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:f4e316d41aa2439337c80aa0a7dfed2cd1f8f3fef42c9b701885d1d7ae3326a5

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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

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

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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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raw_fallback, observed 2026-08-09T20:47:54.584567Z

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

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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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.695861Z digest=sha256:01a004f7f76e84eed644ef29834ba8dc61f8625c55c21d9a539c01787fdea868

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.699977Z digest=sha256:47f09eae73078aa0dfb12eadc62ec49f4461d64cb4e3340bca0bc2c79ee9cc14

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.703750Z digest=sha256:4de6e35cc02e50aecb92da851a15d8ca4507a22b4fd9b3e94b99ff36de975641

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.707402Z digest=sha256:5c0f4b04ccd5ea6f41a3c1c3bbbd454da86a5cd9c760043de128c11cf0e222c6

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.711153Z digest=sha256:1a360d85233415eab62a9c522d1a5fca90eb1ced7c45f97a692f5dc7d41b1e77

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.715437Z digest=sha256:7cdb722fdb3815043f40d817fb59e167dcc346b8c59d76b2810dc0d2494409da

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.719308Z digest=sha256:ec0713e5d4a3be6f7d597ae8f63ddb0816de08b0657562de7ed8f974845d7804

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.722879Z digest=sha256:d2aac9c2582ab523a2d566dd434838d197c3261fc9e5da854f077b81bf471fe2

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.726280Z digest=sha256:06f859bdf8ae5ebf428f315f73f01cc6b3e5ff314ecd2fb48a12fac66e819cc1

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.729889Z digest=sha256:2a9e6e9066dd9f8ab809dd3f97da9a1258b24b7a79ec60978d9256481b711947

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.733476Z digest=sha256:fc426d5b519d524820b759fa392701beddeaa7642a2a993b86b95228435ed85b

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-09T20:47:53.736977Z digest=sha256:cb04001a1de95f79717552ce669f92540e7150bfa019e7289a2fce74f397935d

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=sha256:0c7773845fd4d95aa5438c455ddcc2d5502e7da0d76511145a2768fcff1fbe26

Pith citing papers

No inbound Pith citation observations are available.