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Paper Citation Record · LEDGER

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.13998.

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

pith.paper-citation-record.v1
2412.13998 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:02:42.399277Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:34:26.163405Z

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 8acdb000-0686-4932-9d12-8726a2b6d43c · inbound

Activation Reward Models for Few-Shot Model Alignment cites this paper.

Activation Reward Models for Few-Shot Model Alignment Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T21:02:42.399277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:02:42.399277Z digest=sha256:8698804a4af1fbc50b3afa72e987fabfec02cd20ea9d7cbdbc268d5927f774c2

Observation 4e12ffca-9b85-4c25-ba3e-61cd0bbcb210 · 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 Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:34:26.167583Z

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.

source=pdf_text observed=2026-08-06T16:34:25.069706Z digest=sha256:8dbfeaf906536642a30f6f9e96800fe19f4fef6a53bb84a2d32bf76c465c5a17