Pith. sign in

Paper Citation Record · LEDGER

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2608.03550.

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

pith.paper-citation-record.v1
2608.03550 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:02:19.968492Z

measured 22 of 22 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

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dae44b83-c208-4f24-a9cb-c815c669ba7b · outbound

This paper cites Advances in neural information processing systems , volume=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Advances in neural information processing systems , volume=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.607582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.607582Z digest=sha256:ad2a7fccc9ad3a95f6277ba716e7b048111d16657c2df08701ae7dd899e3afb9

Observation a1a67a53-9e59-41b1-ac60-86a35eb639c8 · outbound

This paper cites Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.680880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.680880Z digest=sha256:0eea1a732b3b5c191eecca914282e4cfa04016aaaac56ebd3c2ebecd47a5d37e

Observation 3221320d-c324-4749-aabc-cbcdf55d781e · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.814349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.814349Z digest=sha256:5badfa63d0ab68ce3f2312e4bd33e5377f91ab9cadc3776214acdf0b4cd0c4d7

Observation caed5d1f-ff83-4456-838e-997bfd39d249 · outbound

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

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.834684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.834684Z digest=sha256:d5840131549d212db87a39fde4ea57466c2f1f4273b2451faaef7c354ff3b07e

Observation 4f4de3a5-eaed-4994-b4af-8938e3c89108 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Training Verifiers to Solve Math Word Problems

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.884527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.884527Z digest=sha256:20127a7aa46464f970f3442f287c7843dce5ddaa1838354fee29f66f8d06d5ef

Observation 368ff1e9-e0cb-4afa-98dc-156dae1264b1 · outbound

This paper cites Advances in neural information processing systems , volume=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Advances in neural information processing systems , volume=

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.890353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.890353Z digest=sha256:452370715d825f7b84bc755e944af9e6a922c915c0f0ecf21e2ee6a9466e937e

Observation 7dba256d-8c71-434a-9807-c41367957286 · outbound

This paper cites AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T17:02:20.256000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T17:02:19.901794Z digest=sha256:b3af3851e003eb7741334ce8ff243a6d2af54055a06818c4de5d26bc209740a2

Observation fe2199e2-3754-49f5-b5cb-9687fd7b15fc · outbound

This paper cites Can LLMs Learn from Previous Mistakes? Investigating LLMs' Errors to Boost for Reasoning.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Can LLMs Learn from Previous Mistakes? Investigating LLMs' Errors to Boost for Reasoning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.907012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.907012Z digest=sha256:f600030f6386449181affba9f06779a8ecad129bce41397b4a68ddf01d17cdca

Observation f92fcb52-e322-4e68-a7ce-cd055346e791 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Measuring Mathematical Problem Solving With the MATH Dataset

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.911541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.911541Z digest=sha256:2330716ccb9e32bba3b637318aa14f63aad97c82cbc4cb9f970be8fac3aa4236

Observation df553d8a-1d2e-44f5-a606-aa81c49702e6 · outbound

This paper cites Qwen2.5 Technical Report.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Qwen2.5 Technical Report

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.916016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.916016Z digest=sha256:1befb9000ab6b207639100a5f81ebdee01a726372418cc5752f9802abce0b7d0

Observation 7db83e26-4656-46bd-8af6-598091389cee · outbound

This paper cites 2024 , howpublished =.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve 2024 , howpublished =

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.920866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.920866Z digest=sha256:cd5d647202128cf3526f5c4c8c80ab87ac344d2333b4dc9f295caf5f303514ca

Observation 40b8d557-0ea9-4bb7-930f-8b1664645473 · outbound

This paper cites 2024 , howpublished =.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve 2024 , howpublished =

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.925372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.925372Z digest=sha256:5cfcd249fce0cab60aa90ee372a90ca2ed5cbddd540b0153a66905cf9461f586

Observation 3f745c18-714c-45c4-a704-e3f248f7a4c6 · outbound

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

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Automatic Chain of Thought Prompting in Large Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.929652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.929652Z digest=sha256:2fd543ee0b36d63623b58e0f8873890e0d2016dd39a8af22e4f1d26c2cb4d462

Observation 8d16c4a2-c911-403b-afe9-35d7da77b739 · outbound

This paper cites Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd workshop on knowledge extraction and integration for deep learning architectures , pages=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd workshop on knowledge extraction and integration for deep learning architectures , pages=

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.934493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.934493Z digest=sha256:ade215b02d1d435e55e0886296c158f0c2f8ec7bbaf88336d17f6bb6e82807d1

Observation 12fda6a4-36fb-467c-8379-b9fd3d876a64 · outbound

This paper cites Proceedings of the 2022 conference of the North American chapter of the association for computational linguistics: human language technologies , pages=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Proceedings of the 2022 conference of the North American chapter of the association for computational linguistics: human language technologies , pages=

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:02:20.375718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T17:02:19.938700Z digest=sha256:1e91b05860de30c88702bcb24fb692a878ba049fa24b6a2fdb57475afc77b9c2

Observation dbc32234-0613-4f73-8da9-ef08a08d34a1 · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.942892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.942892Z digest=sha256:b94da7c3892bc0a997a9979ab3ffec9572cf6cff330b3dbf0128eb081a9895d8

Observation 3f0140d6-2679-46b0-a2af-e423d62d638d · outbound

This paper cites ACL , year=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve ACL , year=

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:02:20.359523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T17:02:19.947552Z digest=sha256:5a885782dec33d5249351070a6531172242c3ffb4245de4670d2f7744f869912

Observation 1cc58c19-93d2-4843-8d53-692c165d2dd3 · outbound

This paper cites Complexity-Based Prompting for Multi-Step Reasoning.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Complexity-Based Prompting for Multi-Step Reasoning

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.951507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.951507Z digest=sha256:41d86ed3f20cd4bcf62959991547954736d5a81a0a0453e59819d4f8701784d8

Observation cd1c9ce4-242c-438e-9814-c4ce3a257eb6 · outbound

This paper cites International Conference on Machine Learning , pages=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve International Conference on Machine Learning , pages=

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:02:20.344650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T17:02:19.955911Z digest=sha256:64afab0226dc5eb2884826eae5429e5f2289ac4ebd4a4b9e023e75a1a3befa2c

Observation c28b1129-6d97-4bd3-83c6-ecd54b0e3b54 · outbound

This paper cites Advances in neural information processing systems , volume=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Advances in neural information processing systems , volume=

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.960562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.960562Z digest=sha256:d425dcb7c56383645cae0b1d1f9ef5de1955877efdcbc5beca53498ea8259ced

Observation 7ba1f97c-916a-4e97-a034-c1dcea7625e3 · outbound

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

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve Active Prompting with Chain-of-Thought for Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.964462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.964462Z digest=sha256:1fd5322089b2a8aa97b37fe79fd814d0dcbb80316f006dcec10601f436b81e4d

Observation 8becad23-d3de-4dfd-be07-e7102154aebd · outbound

This paper cites arXiv preprint arXiv:2506.14641 , year=.

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve arXiv preprint arXiv:2506.14641 , year=

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T17:02:19.968492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:02:19.968492Z digest=sha256:e5aef4356fa3e9da89b8707d51d3fba45c5733bad3848e89a3677c5b43111eb5

Pith citing papers

No inbound Pith citation observations are available.