Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Making Large Language Models Better Reasoners with Alignment
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2309.02144.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T12:47:56.368969Z
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 2026-08-07T06:34:17.273281+00:00.
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 2026-08-07T06:34:17.273281+00:00.
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 2026-08-07T06:34:17.273281+00:00.
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 2026-08-07T06:34:17.273281+00:00.
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 2026-08-07T06:34:17.273281+00:00.
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 2026-08-07T06:34:17.273281+00:00.
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 2026-08-07T06:34:17.273281+00:00.
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.
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.