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Paper Citation Record · LEDGER

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.20500.

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

pith.paper-citation-record.v1
2607.20500 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:39:45.091775Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 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

42 of 42 outbound references displayed

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  • verified fuzzy0
  • unresolved40
  • parse uncertain0
  • malformed identifier0
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Outbound references

Observation 78e84707-91d3-436e-abbc-4fae94947b45 · outbound

This paper cites Agent alpha: Tree search unifying generation, exploration and evaluation for computer-use agents.arXiv preprint arXiv:2602.02995, 2026.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Agent alpha: Tree search unifying generation, exploration and evaluation for computer-use agents.arXiv preprint arXiv:2602.02995, 2026

Reference 1

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source=pdf_text observed=2026-08-02T10:39:40.288340Z digest=sha256:b7de4af633939cf932f4ec79dc0a9c4ba3f5ac48ad43d0873d90bde26d8a1f5e

Observation 67f8409c-417e-4100-b73f-ce4516356bf3 · outbound

This paper cites MINT: Minimal Information Neuro-Symbolic Tree for Objective-Driven Knowledge-Gap Reasoning and Active Elicitation.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts MINT: Minimal Information Neuro-Symbolic Tree for Objective-Driven Knowledge-Gap Reasoning and Active Elicitation

Reference 2

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source=pdf_text observed=2026-08-02T10:39:40.786169Z digest=sha256:a7f818c80aab008e4ecc28cdb6269f4b2ce300879d25f0250e65426eb6303331

Observation 4d0a809b-b739-4f02-8cd8-b5dcb21c2c15 · outbound

This paper cites Agentic ai for cyber defense: Llm-guided hierarchical multi-agent reinforcement learning.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Agentic ai for cyber defense: Llm-guided hierarchical multi-agent reinforcement learning

Reference 3

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source=pdf_text observed=2026-08-02T10:39:40.961280Z digest=sha256:2a96ef8e0f27a97eef1611cad04aaddc3425cc51169d8021ac1d2f996f4985a5

Observation 32377c4b-0ede-4256-9a68-3ab688476fde · outbound

This paper cites Metric-Gradient Projection for Stable Multi-Agent Policy Learning.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Metric-Gradient Projection for Stable Multi-Agent Policy Learning

Reference 4

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source=pdf_text observed=2026-08-02T10:39:41.077110Z digest=sha256:2d0fd67787a59907ae82dc2b0dddf2baf9dc52945f7996a571a0420f79b84aef

Observation b8ccb95a-5c08-46e3-9de3-276edf410364 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Training Verifiers to Solve Math Word Problems

Reference 5

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source=pdf_text observed=2026-08-02T10:39:41.250960Z digest=sha256:3b06638b0cf72bb069ece4b271c24a0e78a88e78b6818bdecffe127096598bfe

Observation 50a4da31-6ff6-4fb7-bb74-6462bfb4ccb1 · outbound

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

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Chain-of-thought prompting elicits reasoning in large language models

Reference 6

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source=pdf_text observed=2026-08-02T10:39:41.428722Z digest=sha256:c4fca05a67ea9c1b6f0c3a83fc35210fbd129e6d6f7b3e48eb2a6e184362053c

Observation 9b3f5f4b-6a30-43a8-9330-80c39ef3c116 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 7

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source=pdf_text observed=2026-08-02T10:39:41.609569Z digest=sha256:eda7fa6dfac85c9b9a92118d0a3603920206446faa16e3634240547236665bf0

Observation 1a14c48f-d078-496a-827a-83ff6a340004 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 8

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source=pdf_text observed=2026-08-02T10:39:41.832552Z digest=sha256:1333d3be234f619d3b884f840c6a437dd3f9e51583f36310b5ece7f5289c5d4f

Observation 0ccded01-944d-4bb4-a7d3-c8264c0146ab · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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source=pdf_text observed=2026-08-02T10:39:41.973044Z digest=sha256:18c80f98adc1edee1e53e914816fd410d23c55b9735f79fb2a9a5b9da22aad3a

Observation 15d28ac2-b261-4533-bae3-f9c659c8518b · outbound

This paper cites Exploring the compositional deficiency of large language models in mathematical reasoning through trap problems.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Exploring the compositional deficiency of large language models in mathematical reasoning through trap problems

Reference 10

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source=pdf_text observed=2026-08-02T10:39:42.127450Z digest=sha256:abf478d80ba24919876765d043375e5a59d43173ea0401d54c94fd55c3178c82

Observation fd78620e-0384-47ec-b7d8-d26ef0f6d0fa · outbound

This paper cites Large language models struggle with unreasonability in math problems.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Large language models struggle with unreasonability in math problems

Reference 11

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source=pdf_text observed=2026-08-02T10:39:42.251636Z digest=sha256:ff0835492e75f20c0caee38bf31e73c6f471132bf9ae5194eb539d6b5fece2a2

Observation e2ac484b-6fb9-43fc-9149-800b418d3fc6 · outbound

This paper cites Vcsearch: Bridging the gap between well-defined and ill-defined problems in mathematical reasoning.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Vcsearch: Bridging the gap between well-defined and ill-defined problems in mathematical reasoning

Reference 12

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source=pdf_text observed=2026-08-02T10:39:42.366897Z digest=sha256:6198acecffd9e22e25dd71ef10a29ea98706a2c52de0379a394c72d9a4aacab5

Observation 705ed944-ebf1-4c9d-afc3-e084db6bb373 · outbound

This paper cites Questbench: Can llms ask the right question to acquire information in reasoning tasks?arXiv preprint arXiv:2503.22674, 2025.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Questbench: Can llms ask the right question to acquire information in reasoning tasks?arXiv preprint arXiv:2503.22674, 2025

Reference 13

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source=pdf_text observed=2026-08-02T10:39:42.496638Z digest=sha256:96632bb45ae7e7b7b576d96e20d7edc735f67b401b173851d51ccddd131b44d4

Observation ff8208a3-a252-456a-8449-9ba5a728fcc4 · outbound

This paper cites Reliablemath: Benchmark of reliable mathematical reasoning on large language models.arXiv preprint arXiv:2507.03133, 2025.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Reliablemath: Benchmark of reliable mathematical reasoning on large language models.arXiv preprint arXiv:2507.03133, 2025

Reference 14

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source=pdf_text observed=2026-08-02T10:39:42.608879Z digest=sha256:9e176a27b954c8f622d45496a290f34d818205bc420c4ec2ec72d5bb04ac5c33

Observation 425b1783-1509-4175-80d6-264c61199f17 · outbound

This paper cites an unresolved cited work.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Unresolved cited work

Reference 15

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Observation aebff015-4961-4c7e-8798-4d3b66002746 · outbound

This paper cites Defining tools to address over- constrained geometric problems in computer aided design.Comput.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Defining tools to address over- constrained geometric problems in computer aided design.Comput

Reference 16

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Observation e24e4d94-30e3-443e-b3b6-514e24c11979 · outbound

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FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Unresolved cited work

Reference 17

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Observation ef9e3416-f018-4e46-84ca-f1683b646601 · outbound

This paper cites Know what you don’t know: Unanswerable ques- tions for squad.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Know what you don’t know: Unanswerable ques- tions for squad

Reference 18

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Observation 7b936e56-18d2-4dc9-b823-2551c37da806 · outbound

This paper cites Language Models (Mostly) Know What They Know.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Language Models (Mostly) Know What They Know

Reference 19

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Observation efe03437-9d62-4332-bd70-3e38135610e1 · outbound

This paper cites Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation

Reference 20

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Observation 97c60765-a27a-4f52-ae3d-1346658d065a · outbound

This paper cites Teaching Models to Express Their Uncertainty in Words.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Teaching Models to Express Their Uncertainty in Words

Reference 21

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source=pdf_text observed=2026-08-02T10:39:43.385592Z digest=sha256:8f44f3ca8097a7e7530cf372d5eef72f84ff1d12effffae26e7961b735f9b5f9

Observation 15eccb68-e8ae-4a0d-b2af-0e07de6f6266 · outbound

This paper cites The pitfalls of next-token prediction.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts The pitfalls of next-token prediction

Reference 22

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Observation d402c2e7-aa95-40d5-a0fa-6f80852386d1 · outbound

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

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 23

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Observation c12a464b-9217-43af-a79b-a24cdaaa9660 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023

Reference 24

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Observation e5b5308e-d4c5-476d-a495-9077d8233f53 · outbound

This paper cites Pal: Program-aided language models.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Pal: Program-aided language models

Reference 25

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Observation c6212f75-938a-4705-87ef-2c342547f25d · outbound

This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 26

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Observation e36c7d07-075f-490f-8d49-689d9eccaa88 · outbound

This paper cites Reason in Chains, Learn in Trees: Self-Rectification and Grafting for Multi-turn Agent Policy Optimization.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Reason in Chains, Learn in Trees: Self-Rectification and Grafting for Multi-turn Agent Policy Optimization

Reference 27

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source=pdf_text observed=2026-08-02T10:39:43.736293Z digest=sha256:039e04b27a0acfd60a97e8d213e8bb4503b24e534280a43689c751d86f8eb262

Observation 87887cfc-5e6e-4386-a2de-6204413ba7b4 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 28

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Observation b0050b7f-aa92-4174-99dc-fa140377f97e · outbound

This paper cites rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 29

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source=pdf_text observed=2026-08-02T10:39:43.845284Z digest=sha256:01208893bd390ccf7fe2891fbf90c1ccabb3c90b0ab0acb656b33084c0275129

Observation 1f0e8632-ba8d-4bc4-84e2-963ba3751ff5 · outbound

This paper cites Interactive Critique-Revision Training for Reliable Structured LLM Generation.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Interactive Critique-Revision Training for Reliable Structured LLM Generation

Reference 30

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Observation c324288c-384b-4210-a915-c4577ef7065e · outbound

This paper cites R-tuning: Instructing large language models to say ‘i don’t know’.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts R-tuning: Instructing large language models to say ‘i don’t know’

Reference 31

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source=pdf_text observed=2026-08-02T10:39:43.955368Z digest=sha256:388f92c62e450ce822914ed7e37d257972720cf942df157a273ec00c775b88fa

Observation 092635f9-75b6-42d3-97ac-8b5389caa236 · outbound

This paper cites On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems.Theoretical Computer Science, 209(1-2):237–260, 1998.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems.Theoretical Computer Science, 209(1-2):237–260, 1998

Reference 32

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source=pdf_text observed=2026-08-02T10:39:43.967877Z digest=sha256:bfde0816df8f241cfffc5247d888fbc94054702159ec255e3c7f2a5f8a30e9e9

Observation afa533e1-a57e-4e94-9667-a09bdc43e885 · outbound

This paper cites Fast heuristics for the maximum feasible subsystem problem.INFORMS Journal on Computing, 13(3):210–223, 2001.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Fast heuristics for the maximum feasible subsystem problem.INFORMS Journal on Computing, 13(3):210–223, 2001

Reference 33

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source=pdf_text observed=2026-08-02T10:39:44.036652Z digest=sha256:aabdbc6256b28aeded3f65fa9ba98c396c9e6ec115cae7f29d5e187176049e75

Observation 46ede77c-43d4-4873-ae9b-3e734ec10aff · outbound

This paper cites Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981

Reference 34

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Observation 98f6bd73-4969-4a86-a76a-74160e3493c7 · outbound

This paper cites A randomized kaczmarz algorithm with exponential convergence.Journal of Fourier Analysis and Applications, 15(2):262–278, 2009.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts A randomized kaczmarz algorithm with exponential convergence.Journal of Fourier Analysis and Applications, 15(2):262–278, 2009

Reference 35

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source=pdf_text observed=2026-08-02T10:39:44.284761Z digest=sha256:a3de51f56a8884e1d99dc357f814ca7b04c08b2b855784126918d3bfb762d697

Observation 6fa39414-eef9-48b1-b5ef-61297d12fb1d · outbound

This paper cites A subspace constrained randomized kaczmarz method for structure or external knowledge exploitation.Linear Algebra and its Applications, 698:220–260, 2024.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts A subspace constrained randomized kaczmarz method for structure or external knowledge exploitation.Linear Algebra and its Applications, 698:220–260, 2024

Reference 36

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source=pdf_text observed=2026-08-02T10:39:44.374532Z digest=sha256:13d0e56d9baa1edacf0e670648005c4382f89621bd554208d1f5fbb36403c735

Observation ccbbf136-55da-458d-9f61-1a7591a7b3f5 · outbound

This paper cites Bert rediscovers the classical nlp pipeline.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Bert rediscovers the classical nlp pipeline

Reference 37

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no resolver link, observed 2026-08-02T10:39:44.548458Z

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source=pdf_text observed=2026-08-02T10:39:44.548458Z digest=sha256:ed235be1c8457385632889539864f2a4bd84db675ed9ed53f2169b2298da5ac1

Observation d0580891-afbf-41b3-8d8a-b7c567f0118f · outbound

This paper cites an unresolved cited work.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Unresolved cited work

Reference 38

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no resolver link, observed 2026-08-02T10:39:44.688036Z

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source=pdf_text observed=2026-08-02T10:39:44.688036Z digest=sha256:9601a440bfb0e90fe6b6a7fe6281170c9071603a5624cc2cae14d2863d215a4a

Observation add6218f-ead1-42cc-aeb9-930250108924 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Representation Learning with Contrastive Predictive Coding

Reference 39

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no resolver link, observed 2026-08-02T10:39:44.802966Z

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source=pdf_text observed=2026-08-02T10:39:44.802966Z digest=sha256:a175a63c6247da74e5a275ce67b06128fed608931777d0f4442935df9d24de98

Observation d1f1f9a4-aa1a-4e3c-9029-0f78f9df5e8b · outbound

This paper cites Club: A contrastive log-ratio upper bound of mutual information.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Club: A contrastive log-ratio upper bound of mutual information

Reference 40

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source=pdf_text observed=2026-08-02T10:39:44.911534Z digest=sha256:a169205b89c04fd924412b5af70f9b1cea200f1b236e1446d67fa8502c66a342

Observation 8e9b80f4-129a-426f-b496-58f44a13e3dd · outbound

This paper cites Qwen3 Technical Report.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts Qwen3 Technical Report

Reference 41

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no resolver link, observed 2026-08-02T10:39:44.983565Z

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source=pdf_text observed=2026-08-02T10:39:44.983565Z digest=sha256:bd496bbb98b602967f69dc62af2104fa3d28342e94dfa56bf8b35c2998b8d7f6

Observation 348534fb-c05a-4162-a9a1-f0c3cf015263 · outbound

This paper cites id": "sample_2368.

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts id": "sample_2368

Reference 42

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no resolver link, observed 2026-08-02T10:39:45.091775Z

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source=pdf_text observed=2026-08-02T10:39:45.091775Z digest=sha256:3ad6ab0328e467e20a7c302bd6d2d55f320140a1f658eedeb8576777982189d3

Pith citing papers

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