Paper Citation Record · LEDGER

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

As of 15 August 2026, this Paper Citation Record lists 28 of 28 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 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:38:43.203572Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

28 of 28 outbound references displayed

verified exact1
verified fuzzy4
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 43689ceb-c541-4db3-b210-86441f99eeb6 · outbound

This paper cites write newline.

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

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.374266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 250908ab-3120-4f44-8c85-56326a1db72a · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.420860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad1e4c42-4b68-4d93-ade1-8f6705b801c9 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Constitutional AI: Harmlessness from AI Feedback

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.432089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a26b12ce-55ee-4cc0-ac18-8e93e5019c61 · outbound

This paper cites Pareto-Optimal Learning from Preferences with Hidden Context.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Pareto-Optimal Learning from Preferences with Hidden Context

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:38:43.254158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c9dcdbbf-3471-4d72-9556-16611bf5b0a1 · outbound

This paper cites an unresolved cited work.

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

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.449622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c046b64a-76df-4ac3-becd-caba3cc8f1f9 · outbound

This paper cites V., and Syrgkanis, V.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes V., and Syrgkanis, V

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.455651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27a85868-da9c-4cbf-b000-666680618db7 · outbound

This paper cites UltraFeedback: Boosting Language Models with Scaled AI Feedback.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes UltraFeedback: Boosting Language Models with Scaled AI Feedback

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.460776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9966b605-cc5a-40fd-a080-678a3f0bdd6d · outbound

This paper cites W., Rezende, D., and Eslami, S.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes W., Rezende, D., and Eslami, S

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:38:44.145821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation deb0e917-eefd-4d4f-bc5a-1d50bafec7a7 · outbound

This paper cites Neural Processes.

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

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.542225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 528954e4-c12f-4004-b160-bd3384c4d079 · outbound

This paper cites Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.606208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba85029f-7f41-4750-bb58-e62d39f7e4e9 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes LoRA: Low-Rank Adaptation of Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.687841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdb0deea-a249-478e-8cc3-65d4c56f5484 · outbound

This paper cites Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.693809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9259effb-283c-4e17-a72e-1a043393b3f2 · outbound

This paper cites Preference Transformer : Modeling Human Preferences using Transformers for RL.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Preference Transformer : Modeling Human Preferences using Transformers for RL

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:38:43.954124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 649ec6cd-7114-4f2c-893e-5699022ca650 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Adam: A Method for Stochastic Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.704373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0e15f9e-bd09-49f0-92b1-4f4d3adfcc70 · outbound

This paper cites Training language models to follow instructions with human feedback.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Training language models to follow instructions with human feedback

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.709208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d39d24ee-4f7c-4713-96aa-8e4d92794d4b · outbound

This paper cites Automatic differentiation in pytorch.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Automatic differentiation in pytorch

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.715496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 640a6259-da4a-4a4d-ad6f-e33fabf67bcf · outbound

This paper cites FiLM: Visual Reasoning with a General Conditioning Layer.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes FiLM: Visual Reasoning with a General Conditioning Layer

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.720440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 025fb091-50e1-4470-a2b2-e333053699b1 · outbound

This paper cites Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.725901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3aca3f66-cddd-4ac6-95f2-b1d7bc3ba8f0 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.732968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 381a1218-56d0-47fc-bfa7-658bb07a7b81 · outbound

This paper cites Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.778618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 162becfb-7cf4-4aae-9f36-4588d7d45ddf · outbound

This paper cites DISTRIBUTIONAL PREFERENCE LEARNING : UNDERSTANDING AND ACCOUNTING FOR HIDDEN CONTEXT IN RLHF.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes DISTRIBUTIONAL PREFERENCE LEARNING : UNDERSTANDING AND ACCOUNTING FOR HIDDEN CONTEXT IN RLHF

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:38:43.874000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 07f9abf7-96ec-4007-a446-4ed10da6cfdc · outbound

This paper cites A Roadmap to Pluralistic Alignment.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes A Roadmap to Pluralistic Alignment

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:42.918505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e27b4d01-c81a-416c-b870-d071856d62b4 · outbound

This paper cites M., Lowe, R., Voss, C., Radford, A., Amodei, D., and Christiano, P.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes M., Lowe, R., Voss, C., Radford, A., Amodei, D., and Christiano, P

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:38:43.854661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation da1bb913-e86b-4ec3-a51c-8e5b0c49a762 · outbound

This paper cites Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:43.118721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7225a9a4-7606-4b12-81ed-c638cc3613ac · outbound

This paper cites Conditional Language Policy: A General Framework for Steerable Multi-Objective Finetuning.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Conditional Language Policy: A General Framework for Steerable Multi-Objective Finetuning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:43.187939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 286c9f84-ce67-4444-8e5b-41ba393b1719 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:43.193545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7dc0ca9-b69e-47a1-b330-91bd90b61821 · outbound

This paper cites Deep Sets.

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

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:43.198497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd68763f-dc41-4f9f-aaed-8695034a5913 · outbound

This paper cites Panacea: Pareto Alignment via Preference Adaptation for LLMs.

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes Panacea: Pareto Alignment via Preference Adaptation for LLMs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T12:38:43.203572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-15T06:32:42.880941+00:00.