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Paper Citation Record · LEDGER

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning

As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2507.00214.

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

pith.paper-citation-record.v1
2507.00214 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:24:15.098291Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:19:38.838228Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T04:20:38.770680Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 68c0f5d8-697f-4d1e-adbb-e7c39f09bca1 · outbound

This paper cites Meta llama 3.2: A 1.4t parameter class of language models.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Meta llama 3.2: A 1.4t parameter class of language models

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:17.583559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:13.550165Z digest=sha256:8e578d908ec957bbf0107893047a74b7d71a2435bb074f10844068685cd68a59

Observation 0c31d66a-8405-4512-be6f-4d5cb26628ff · outbound

This paper cites Language Models are Few-Shot Learners.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Language Models are Few-Shot Learners

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T21:24:13.668124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:13.668124Z digest=sha256:885063c080fd996fa0a10016984a61dbcff88f63f2d560fed68a9ef39298fc7a

Observation 80e9fbb4-04b0-4111-b6bb-22b9cc2c555e · outbound

This paper cites e-snli: Natural language inference with natural language explanations.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning e-snli: Natural language inference with natural language explanations

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:17.278400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:13.841196Z digest=sha256:16795c2666a2df773246ffc6fa0ba89d77ffd7cdf160a9d3e1a0cb3f3ebff320

Observation aede28e9-e95e-46b4-855b-40ecd1e14082 · outbound

This paper cites Speech and language processing: An introduction to natural language processing, computational linguis- tics, and speech recognition.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Speech and language processing: An introduction to natural language processing, computational linguis- tics, and speech recognition

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:17.028383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:13.966008Z digest=sha256:5e60e632c42e73681b135430b604e2d534dadc5955727dde35da2a73fc9839fb

Observation d3b1d927-3db0-4c6b-b3a0-9acacc65efac · outbound

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

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Large Language Models are Zero-Shot Reasoners

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T21:24:14.106002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:14.106002Z digest=sha256:f0223cd7efac579475ccc116f6ffbc29b2f2bb61ecf5c465a937766a8a09d47d

Observation 40d361ea-56f6-49e0-a15c-44f370f7add3 · outbound

This paper cites Rationalizing neural predictions.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Rationalizing neural predictions

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:16.788093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:14.261798Z digest=sha256:6b3dbd1567a6a832ca227d27e8078a5056571d17479a0791b7f5a936c963dda3

Observation 8fb9bdad-175f-4d4f-84f0-9225a02e83c4 · outbound

This paper cites Explain yourself! : Leveraging language models for faithful rationalization.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Explain yourself! : Leveraging language models for faithful rationalization

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:16.489705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:14.406188Z digest=sha256:69bc8b31131dbdd35b6ea6561e3cc0d715f9edde982e1f1a006ec684d2c157f1

Observation 1f29e859-432e-4006-929a-2e87d373e5ae · outbound

This paper cites ”why should i trust you?”: Explaining the predictions of any classifier.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning ”why should i trust you?”: Explaining the predictions of any classifier

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:16.207005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:14.555815Z digest=sha256:136f8546465c76dbd46bea2c3a3389da6e2947b446ccc816c318773e0df22699

Observation c16c6999-ecf5-49fa-9049-7a578abee7de · outbound

This paper cites A survey on image data augmentation for deep learning.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning A survey on image data augmentation for deep learning

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:15.913864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:14.687108Z digest=sha256:b44a8bd122768acd7e3393054e39f9fbdbbebedff5a23d6c0fff6829184910d0

Observation 11ec0221-b304-4f83-b3be-d36443d31fa7 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning LLaMA: Open and Efficient Foundation Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T21:24:14.795218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:14.795218Z digest=sha256:79d903992a1c658cd41e2c2661ecfbe7ff37d47b0a633f5f3fb88ce886640337

Observation b3869cd2-f97b-4392-9b48-9a003c7a6a40 · outbound

This paper cites Chain-of-thought prompting elicits rea- soning in large language models.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Chain-of-thought prompting elicits rea- soning in large language models

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:15.588195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:14.937937Z digest=sha256:ddf786a70a424ea51366135c034eeca301dff054f2f414ae4b9c4cc8a6ec2e34

Observation a3bf2887-271a-43c9-8933-374b8833e871 · outbound

This paper cites Spiraling of sub-Riemannian geodesics around the Reeb flow in the 3D contact case.

Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning Spiraling of sub-Riemannian geodesics around the Reeb flow in the 3D contact case

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T21:24:15.341675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:15.098291Z digest=sha256:f0ee64b2a8dc824733962dd551ea46dc4fec88d9f4ab57259e1eaf7e15ab0166

Pith citing papers

Observation 9e0e56dc-e793-4bab-aeee-06f6687bb1b0 · inbound

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques cites this paper.

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:20:38.775257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T04:20:37.465711Z digest=sha256:c9331271f2be38aad9e21bde51a208a8de242cab1721e9d28910a3e8169406ea

Observation 875fdb2c-3ae5-4bed-9f40-11169a2a50a6 · inbound

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques cites this paper.

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques Two-Stage Reasoning-Infused Learning: Improving Classification with LLM-Generated Reasoning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T04:19:38.838228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T04:19:38.838228Z digest=sha256:96afcf3f6077b68deaef95ce9dc7f42b69ad1c0e8d0a6bdd83d7d2a984a857f6