Paper Citation Record · LEDGER

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models

As of 11 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.14049.

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

pith.paper-citation-record.v1
2607.14049 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:01:43.430128Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

24 of 24 outbound references displayed

verified exact0
verified fuzzy0
unresolved23
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac20d68a-8d2e-4284-a0f9-37a45f2e5860 · outbound

This paper cites an unresolved cited work.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.037869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6179f191-9e5f-4067-9111-a0c035bd03e0 · outbound

This paper cites Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:40.938291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 292b3860-2293-4c10-ab6a-e53838b4ac39 · outbound

This paper cites CoT Edit.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models CoT Edit

Reference 3

Resolution: malformed identifier; no resolver link, observed 2026-08-02T03:01:41.873784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ff5cb73-e32a-4395-afbe-f0ef87e246ee · outbound

This paper cites DeepSeek-V3 Technical Report.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models DeepSeek-V3 Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.103729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca4bd60c-bbe2-44e9-969d-2b5ae40bd0ae · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.215746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8847364-8024-46f3-bfc0-5b616fb8ead4 · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.337331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40198c65-e693-44da-9022-bd9cea74a140 · outbound

This paper cites Branch-Solve-Merge Improves Large Language Model Evaluation and Generation.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Branch-Solve-Merge Improves Large Language Model Evaluation and Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.432644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1af0f6ed-2777-4999-b75d-a4bbafe71b4e · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.499409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85190ce8-e6ed-409c-9ad3-303fe02bcae7 · outbound

This paper cites Co-CoT: A Prompt-Based Framework for Collaborative Chain-of-Thought Reasoning.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Co-CoT: A Prompt-Based Framework for Collaborative Chain-of-Thought Reasoning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.773164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49da11b1-db05-482a-92fa-1084b9fd7258 · outbound

This paper cites For both objects to be in motion with a constant velocity (or at rest) ## 3.A is heavier than B, so for the system,A will carry B in motion.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models For both objects to be in motion with a constant velocity (or at rest) ## 3.A is heavier than B, so for the system,A will carry B in motion

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.150602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23df3647-ab61-4e5a-a184-8e392ce8ccac · outbound

This paper cites ## Query In the figure, Object A weighs 10N and object B weighs 6N.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models ## Query In the figure, Object A weighs 10N and object B weighs 6N

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.329219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d034784-49a3-4681-9e71-1a001afccb61 · outbound

This paper cites Since the gravity of Object A is 10N and friction and the self-weight of the spring scale are not taken into account, the tension on the rope is equal to the gravity of Object A.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Since the gravity of Object A is 10N and friction and the self-weight of the spring scale are not taken into account, the tension on the rope is equal to the gravity of Object A

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.473412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0957075-f3a3-46a4-9bf9-493402d41e17 · outbound

This paper cites an unresolved cited work.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.551563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fd1d54d-bd69-4707-9209-895a6a9aefba · outbound

This paper cites Thus the answer is：6N and 0N Original Query + 1.analyze if equilibrium is possible: a fixed pulley changes the direction of force, not its magnitude.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Thus the answer is：6N and 0N Original Query + 1.analyze if equilibrium is possible: a fixed pulley changes the direction of force, not its magnitude

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.622712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6779dbfa-e995-41b1-9744-5f85ad05cb36 · outbound

This paper cites When A, B are stable, they have the same acceleration.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models When A, B are stable, they have the same acceleration

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.721078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a82d936d-bd3f-48a7-bcbf-8ebec2691e6b · outbound

This paper cites Since the gravity of Object A is 10N and friction and the self- weight of the spring scale are not taken into account, the tension on the rope is equal to the gravity of Object A.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Since the gravity of Object A is 10N and friction and the self- weight of the spring scale are not taken into account, the tension on the rope is equal to the gravity of Object A

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.815121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a921f5a-d14b-40c2-93d4-ec8417ba62cc · outbound

This paper cites 4.Calculate the force on the spring Edited CoT Figure 12: A physics question, and the issue lies in the reasoning process.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models 4.Calculate the force on the spring Edited CoT Figure 12: A physics question, and the issue lies in the reasoning process

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:42.908348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b032507e-d17e-4295-9bf8-016a69a5f1d0 · outbound

This paper cites worker quality.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models worker quality

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:43.020155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e8d7f77-90db-4ab8-931e-a8ab746b604e · outbound

This paper cites weakest.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models weakest

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:43.173935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85732034-a2a8-409a-bc47-2771525c51b1 · outbound

This paper cites still working.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models still working

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:43.298509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5bcda35-f73c-4290-b203-91254d06fd6f · outbound

This paper cites an unresolved cited work.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:43.430128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb056355-4484-4ed2-9a06-9f8609a4436a · outbound

This paper cites InThe Twelfth Inter- national Conference on Learning Representations.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models InThe Twelfth Inter- national Conference on Learning Representations

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.046601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0533e7d-7473-4b5e-bacb-f0655eb0f325 · outbound

This paper cites SWE-Bench+: Enhanced Coding Benchmark for LLMs.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models SWE-Bench+: Enhanced Coding Benchmark for LLMs

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:40.820412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b007d93f-ecba-42dc-810f-f22a70946847 · outbound

This paper cites An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning.

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T03:01:41.653988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.