Paper Citation Record · LEDGER

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths

As of 17 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2412.08281.

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

pith.paper-citation-record.v1
2412.08281 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:06:26.378332Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

16 of 16 outbound references displayed

verified exact0
verified fuzzy8
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0c601f5-7b70-455f-98c3-3e49155aaca6 · outbound

This paper cites Large language models for software engineering: Survey and open problems,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Large language models for software engineering: Survey and open problems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.788000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 12024569-4f1b-4a26-8ae6-2f2abfadf709 · outbound

This paper cites Towards autonomous testing agents via conversational large language models,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Towards autonomous testing agents via conversational large language models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.759145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c87f309-4d5a-43d2-a6bb-2d55a8d60cad · outbound

This paper cites Explainable Automated Debugging via Large Language Model-driven Scientific Debugging.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Explainable Automated Debugging via Large Language Model-driven Scientific Debugging

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.267928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ae02605-88e5-4b50-b39d-fb8c750eb8dc · outbound

This paper cites Swe-agent: Agent-computer interfaces enable automated software engineering,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Swe-agent: Agent-computer interfaces enable automated software engineering,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.738323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 896a6d89-e2b3-4941-b870-25258bdcdea3 · outbound

This paper cites Intent-driven mobile gui testing with autonomous large language model agents,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Intent-driven mobile gui testing with autonomous large language model agents,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.710931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e1b9246-37df-4488-9a51-37264d86feb2 · outbound

This paper cites A quantitative and qualitative evaluation of llm-based explainable fault localization,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths A quantitative and qualitative evaluation of llm-based explainable fault localization,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.297200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 404d68af-bda5-421d-9bac-ed02bb63b46d · outbound

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

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Chain-of-thought prompting elicits reasoning in large language models,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.306711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce04be4e-958c-4ede-8002-efdffa73ae02 · outbound

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

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.312204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42605525-d1f0-41f1-a1fd-0c31ac49260f · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths ReAct: Synergizing Reasoning and Acting in Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.320526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 255b7f3b-5c84-4b06-b0cb-89c245fadb64 · outbound

This paper cites Better patching using llm prompting, via self-consistency,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Better patching using llm prompting, via self-consistency,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.661454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 95b120af-8121-4303-a7e4-8c887a8d2a9f · outbound

This paper cites Energy and policy consid- erations for deep learning in NLP,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Energy and policy consid- erations for deep learning in NLP,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.622663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94d53f9f-4cc2-46bd-8887-006089f4c489 · outbound

This paper cites an unresolved cited work.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:06:26.594321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 623c1438-ff86-4fe1-be33-daa4f5301a5b · outbound

This paper cites Long short-term memory,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Long short-term memory,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.560333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c8fd4d08-23f8-4602-a861-5740f1c2c21d · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Semi-Supervised Classification with Graph Convolutional Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.361634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 809b1d27-1df3-478a-8b66-0dd8405ea6b4 · outbound

This paper cites Bugsinpy: a database of existing bugs in python programs to enable controlled testing and debugging studies,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Bugsinpy: a database of existing bugs in python programs to enable controlled testing and debugging studies,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:06:26.537646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe6a52dc-0625-45b0-81d6-43dd585c81a4 · outbound

This paper cites Defects4j: A database of existing faults to enable controlled testing studies for java programs,.

Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths Defects4j: A database of existing faults to enable controlled testing studies for java programs,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T18:06:26.378332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.