Paper Citation Record · LEDGER

Classifiers are Better Experts for Controllable Text Generation

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2205.07276.

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

pith.paper-citation-record.v1
2205.07276 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:11:25.285084Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:18:57.970921Z

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 f33df39c-d741-408a-a4af-c35351a44b2d · inbound

Controlled LLM Decoding via Discrete Auto-regressive Biasing cites this paper.

Controlled LLM Decoding via Discrete Auto-regressive Biasing Classifiers are Better Experts for Controllable Text Generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T04:11:25.285084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea149cd8-3985-4e73-972f-900d3241831c · inbound

Decoupling Task-Solving and Output Formatting in LLM Generation cites this paper.

Decoupling Task-Solving and Output Formatting in LLM Generation Classifiers are Better Experts for Controllable Text Generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T12:12:57.568087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2fa72b9-2a41-4dc6-b051-19ea13b27f3e · inbound

CLIPer: Tailoring Diverse User Preference via Classifier-Guided Inference-Time Personalization cites this paper.

CLIPer: Tailoring Diverse User Preference via Classifier-Guided Inference-Time Personalization Classifiers are Better Experts for Controllable Text Generation

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:50:54.232669Z

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.

Observation 786a723c-390f-4b20-83c6-e4bf55115e34 · inbound

Multi-Objective Exploration and Preference Optimization via Mutual Information cites this paper.

Multi-Objective Exploration and Preference Optimization via Mutual Information Classifiers are Better Experts for Controllable Text Generation

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:57.973024Z

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.