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Paper Citation Record · LEDGER

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation

As of 16 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2507.09850.

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

pith.paper-citation-record.v1
2507.09850 v3

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:51:18.445576Z

measured 15 of 15 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

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7633559d-e6e7-49d6-8174-061d73ca5f90 · outbound

This paper cites Contrastive Chain-of-Thought Prompting.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Contrastive Chain-of-Thought Prompting

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:16.980286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:16.980286Z digest=sha256:2edcc188716fb2468b55c2c4b55594739a40f5e2f41677c537b31e97d26098df

Observation 6cb8ee24-caf1-4f41-a2c3-d551fbd8ef0c · outbound

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

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.164619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.164619Z digest=sha256:a9bfb3636ccde123e346a533736256c876254dfa99d9664ad1ccdc719d178402

Observation f3944f59-10fc-467b-9455-de2c0df293fd · outbound

This paper cites s1: Simple test-time scaling.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation s1: Simple test-time scaling

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.567757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.567757Z digest=sha256:9fdd5aa29e213870a8220b2310e2dcecef35be7fec74027c17ef4c13f22888e6

Observation 89346af0-55f5-431c-aa5a-9756990d1cbd · outbound

This paper cites Chain-of-Thought Reasoning Without Prompting.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Chain-of-Thought Reasoning Without Prompting

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.807073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.807073Z digest=sha256:2418eb5f3aad3dcf131a64f6d72d44b0da25bdf22174537f157c5e9d9396e271

Observation 7e278407-41c0-471b-9ac3-95814c0ed2ae · outbound

This paper cites Qwen2.5 Technical Report.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Qwen2.5 Technical Report

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.900304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.900304Z digest=sha256:edfef09a0e5227cc55134e299605fe18e79cf1ee10a3f052e1fc98638bedcf63

Observation 4b3b4f80-3ef6-4235-aed0-c9a318962226 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.971403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.971403Z digest=sha256:03296609011f5f87d1ab9e26440e6284952e12c03aa6944f5fd74f37412ec84e

Observation b3ded519-52c8-419b-8937-bbaaa9dccd8a · outbound

This paper cites SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:18.054670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:18.054670Z digest=sha256:5eb1e4f1b4fd2dee467e04f530e5dfd7ee6a12fcbbf9499d854adb2b0a5dcdb9

Observation 5bdb560a-8df6-4ae0-950c-3e6bf4abd00d · outbound

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

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Automatic Chain of Thought Prompting in Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:18.153821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:18.153821Z digest=sha256:20fe7701f1f42c2bb03e7ed44dfac82048944726300c695f26728a5049e145a8

Observation cc35a9d0-f3f1-4a56-9c7b-ef8c73ed6f86 · outbound

This paper cites Data Generation A.1.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Data Generation A.1

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:51:19.010536Z

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=pdf_text observed=2026-08-06T17:51:18.351929Z digest=sha256:378ae75b16a436ab0dff301aa53ecd2c68d69ccfeed7a4acb57dc9bf8e4faddf

Observation 71a31c61-5e24-4cfb-93b8-39259fd68486 · outbound

This paper cites an unresolved cited work.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:51:18.833812Z

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=pdf_text observed=2026-08-06T17:51:18.445576Z digest=sha256:068e11f935859da6c9a6fb5f5171789cc6e7c9d26a5a8dfbb483c7875c419c65

Observation 0d686b90-4d44-4569-aa29-0b00ae6925ff · outbound

This paper cites AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.434256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.434256Z digest=sha256:942395752e121234bc1c19c1d71783a7c03ba130d5dfb7341044d020c8b7762a

Observation 2c81de72-3dc9-445f-bd2f-2f60b4ad8fd7 · outbound

This paper cites 1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation 1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:18.253925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:18.253925Z digest=sha256:fdef2fbd04f0e6ef5eb25da609aacdc2d526deb985e58d720c67d2b445a1a033

Observation a93047fa-a45b-4632-8ee3-edd78f5fda81 · outbound

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

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation Active Prompting with Chain-of-Thought for Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.063408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.063408Z digest=sha256:40dc436479d391c310893cf0831d32a6ab8f7742aba6c90df8d87ac27a77fe14

Observation d6f2d8f8-f5b9-4855-9ecc-2958f85c6327 · outbound

This paper cites NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.701818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.701818Z digest=sha256:d0fa95c23b69cf3a7267cbde50a3ee91f7bd210df4ab192963f520958cf89069

Observation afb432f3-93a1-4898-82d6-2917b06861ec · outbound

This paper cites LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!.

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:17.298387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:51:17.298387Z digest=sha256:ff7d156733f0927481bcc233ebff9e87505b9536fd9e34af0a803ee998f86fd0

Pith citing papers

No inbound Pith citation observations are available.