Paper Citation Record · LEDGER

Towards Efficient Exact Optimization of Language Model Alignment

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.00856.

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

pith.paper-citation-record.v1
2402.00856 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:32:21.045898Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T00:02:24.520070Z

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 42270018-9ef5-4abf-b241-7186c0528296 · inbound

Preference learning made easy: Everything should be understood through win rate cites this paper.

Preference learning made easy: Everything should be understood through win rate Towards Efficient Exact Optimization of Language Model Alignment

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T18:32:21.045898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d205c502-cb5c-4978-aa94-648277d293ff · inbound

Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning cites this paper.

Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning Towards Efficient Exact Optimization of Language Model Alignment

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:40.748666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd1ab393-df0e-4416-a6f6-718ce22906b9 · inbound

MCP Safety Training: Learning to Refuse Falsely Benign MCP Exploits using Improved Preference Alignment cites this paper.

MCP Safety Training: Learning to Refuse Falsely Benign MCP Exploits using Improved Preference Alignment Towards Efficient Exact Optimization of Language Model Alignment

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:11.589423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93a3a016-32f8-40a2-a29d-41d011bc36ec · inbound

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities cites this paper.

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities Towards Efficient Exact Optimization of Language Model Alignment

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:25.054186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a96aa0da-8eff-4ea9-b056-c1e09d4268bd · inbound

Enhancing Small LLM Alignment through Margin-Based Objective Modifications under Resource Constraints cites this paper.

Enhancing Small LLM Alignment through Margin-Based Objective Modifications under Resource Constraints Towards Efficient Exact Optimization of Language Model Alignment

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T21:33:14.147588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 122b1dcd-d851-4dc2-ae4a-45649f9d1c4a · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Towards Efficient Exact Optimization of Language Model Alignment

Reference 231

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:02:24.523411Z

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.

Observation 6fd528bd-c63d-44b0-827e-61bfb90784df · inbound

Leveraging RAG for Training-Free Alignment of LLMs cites this paper.

Leveraging RAG for Training-Free Alignment of LLMs Towards Efficient Exact Optimization of Language Model Alignment

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:42:08.207895Z

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.

Observation 4928998a-6880-4b17-a7bc-fbaa7c2580f0 · inbound

When Policy Entropy Constraint Fails: Preserving Diversity in Flow-based RLHF via Perceptual Entropy cites this paper.

When Policy Entropy Constraint Fails: Preserving Diversity in Flow-based RLHF via Perceptual Entropy Towards Efficient Exact Optimization of Language Model Alignment

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:52:22.210098Z

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.