Paper Citation Record · LEDGER

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies

As of 20 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2507.00606.

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

pith.paper-citation-record.v1
2507.00606 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:16:51.279101Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:17.910805Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T17:54:19.677216Z

Reference resolution

22 of 22 outbound references displayed

verified exact3
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 59fd3df2-b672-4d43-b0ba-6382b55f3e25 · outbound

This paper cites AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:16:54.374748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d1d1994b-29ac-4be4-9e38-04009a6df7ba · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Training Verifiers to Solve Math Word Problems

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.454847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 841b6e45-5948-4218-afa2-84f94372c9da · outbound

This paper cites Meta Reasoning for Large Language Models.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Meta Reasoning for Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.494756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c867d7f-363f-40b5-b10c-b9aaf8c930aa · outbound

This paper cites Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.544901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deff873e-e65f-40ff-b58f-209e733d7bde · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Measuring Massive Multitask Language Understanding

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.584751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd2337c1-b0e5-4be8-b867-53b0f05a25b0 · outbound

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

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Large Language Models are Zero-Shot Reasoners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.644750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ac96c7a-0361-492f-a01a-d090bb8604b8 · outbound

This paper cites Fine-Tuning Language Models with Just Forward Passes.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Fine-Tuning Language Models with Just Forward Passes

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.674772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbbdc3e9-5c8c-413e-9a73-a8e944f3c260 · outbound

This paper cites Qwen2.5 Technical Report.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Qwen2.5 Technical Report

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.724752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56228186-f6f0-48a3-adf0-11911c2a8a2c · outbound

This paper cites Fast Trainable Projection for Robust Fine-Tuning.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Fast Trainable Projection for Robust Fine-Tuning

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:16:53.582618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4a8eb719-95ec-4b58-92c7-61c83ecda080 · outbound

This paper cites DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:16:53.082011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4d9e3b16-a89b-4efe-b75a-9dc6145916c5 · outbound

This paper cites Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.841505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31919994-c69f-4e7e-8882-13e4469f3e71 · outbound

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

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.884768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10d19d9c-c141-405d-ad36-3a7c0e800f53 · outbound

This paper cites Think Twice: Perspective-Taking Improves Large Language Models' Theory-of-Mind Capabilities.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Think Twice: Perspective-Taking Improves Large Language Models' Theory-of-Mind Capabilities

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.934750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37e66f9b-65bf-42f3-a1f8-e4e548700777 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:50.965005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b962d5de-d971-4dd6-8caf-60b31bef2a7b · outbound

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

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.004921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 282c7b19-18be-421a-b86b-57967a2e1301 · outbound

This paper cites Large Language Models as Analogical Reasoners.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Large Language Models as Analogical Reasoners

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.064760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22f83713-35bc-42d8-86ad-dc139b8e3228 · outbound

This paper cites an unresolved cited work.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.104970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36c13163-c5cd-4311-9966-32ef2a0b6fa1 · outbound

This paper cites Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.141936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 503b05a4-1b1c-42ec-ba52-92e8d3456453 · outbound

This paper cites Self-Discover: Large Language Models Self-Compose Reasoning Structures.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Self-Discover: Large Language Models Self-Compose Reasoning Structures

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.175361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc79d848-cf3a-4155-bb70-2cb3ce06f77a · outbound

This paper cites an unresolved cited work.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.214785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8223d0a-5c42-4b69-a58d-32b2788f5b50 · outbound

This paper cites online" 'onlinestring :=.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies online" 'onlinestring :=

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.247417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0669d8b7-b42a-4684-bce9-96fb82609859 · outbound

This paper cites write newline.

Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies write newline

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:51.279101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 38572890-c086-404c-b336-dd1ec431871a · inbound

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey cites this paper.

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey Mixture of Reasonings: Teach Large Language Models to Reason with Adaptive Strategies

Reference 212

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:54:19.792052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.