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Paper Citation Record · LEDGER

Making Large Language Models Better Reasoners with Alignment

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2309.02144.

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

pith.paper-citation-record.v1
2309.02144 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:26:56.266635Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T03:23:49.571699Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 008d00d3-9ae8-46b2-ba24-9919bac0ca63 · inbound

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning cites this paper.

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning Making Large Language Models Better Reasoners with Alignment

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T23:46:39.501439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-17T23:46:39.330438Z digest=sha256:3f13d80ee3c7a5862571f8eeec7236da2259275750c69dd7ef454ef1084983dd

Observation c313013d-4410-4ccf-98b7-131ae7229763 · inbound

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models cites this paper.

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Making Large Language Models Better Reasoners with Alignment

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-05-13T10:07:53.846541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T10:07:53.748795Z digest=sha256:512b37fe82b447a59861a9c3ff03421e2788de83ed796862260e817804cbf22e

Observation c6c64d2c-807a-429a-851a-8d08a585b2ff · inbound

Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations cites this paper.

Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations Making Large Language Models Better Reasoners with Alignment

Reference 84

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T22:34:15.818946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-14T22:34:15.638114Z digest=sha256:28ac6d137fee77aef66d1d3cc72d3bcb84bec11fe6da11dc5793a14171740e3b

Observation 613359b5-d014-40fd-9e4a-830c05c623ec · inbound

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models cites this paper.

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models Making Large Language Models Better Reasoners with Alignment

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:23:49.574772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-24T03:23:18.827351Z digest=sha256:a3684fa419676b988987bfc64751b1ceb3f37a69588dea6118ab4199d00bbd14

Observation c3fdd2a5-3450-469e-98a9-35b0d2c12475 · inbound

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive cites this paper.

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive Making Large Language Models Better Reasoners with Alignment

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:04:44.448082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-17T23:04:44.287660Z digest=sha256:07a89890f2838344340ec7feab536461219a64e7296ff5687957102d83c7a5db

Observation 621b2a06-61ae-4422-ba01-feebf281b7a3 · inbound

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model cites this paper.

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model Making Large Language Models Better Reasoners with Alignment

Reference 174

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:36:26.926578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-11T05:36:26.207359Z digest=sha256:a30a06a0fb49a61649be1a87b9c3f76e00bda570ed358500be39ce6b5c34d844

Observation d3673c36-b155-43a3-a7ac-b846dc343f53 · inbound

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing cites this paper.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Making Large Language Models Better Reasoners with Alignment

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-09T18:26:56.266635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:26:56.266635Z digest=sha256:769647c50db2f51441045c3935e5f79c3fa3fd3dc875c48b105225204889e8f3

Observation 35313d04-0742-432d-a711-1b42a4ae0b89 · inbound

Empowering LLMs in Task-Oriented Dialogues: A Domain-Independent Multi-Agent Framework and Fine-Tuning Strategy cites this paper.

Empowering LLMs in Task-Oriented Dialogues: A Domain-Independent Multi-Agent Framework and Fine-Tuning Strategy Making Large Language Models Better Reasoners with Alignment

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T15:41:10.817384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:41:10.817384Z digest=sha256:bf046c205a04b38f3733b82e4e9757b6a10b35e1caf92874ea90f65076903d77

Observation b3030e9e-68e9-480a-9bf1-70470f0c9d15 · inbound

RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models cites this paper.

RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models Making Large Language Models Better Reasoners with Alignment

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T11:21:42.079243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:21:42.079243Z digest=sha256:68a559b5ce17fdf067878724a7dc1a5d00cffa4fa6fc9525bcdc25294e6b4675

Observation 2d7d8e3f-7de2-4906-9ce9-1d2397627f19 · inbound

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning cites this paper.

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning Making Large Language Models Better Reasoners with Alignment

Reference 259

Resolution
verified exact
arxiv_id, observed 2026-05-19T01:01:10.458067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-19T01:01:09.840919Z digest=sha256:1e7a4a94ff4c781ebc4a780b61354694a5b118206e2fb854e2bc3ccccfa6cdb5

Observation 979b9f9f-457d-40bb-b45b-00bc72a5ce05 · inbound

Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation cites this paper.

Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation Making Large Language Models Better Reasoners with Alignment

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-14T15:30:23.485228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T15:30:23.485228Z digest=sha256:169d9440543095e51d819decd27c961a0f54eb96ded78883d5487b5b8a485ddc

Observation 14f08006-1968-4052-8dcd-74d19b9a8000 · inbound

Lost in Context: Addressing Context Anxiety in Large Language Models cites this paper.

Lost in Context: Addressing Context Anxiety in Large Language Models Making Large Language Models Better Reasoners with Alignment

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T12:47:56.368969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:47:56.368969Z digest=sha256:6e4369d3b10d20ec561c40c94974e6181a9c93f8929edcfdcb2218977cc33e3e