Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2412.04835.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T00:49:36.689172Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T17:22:25.029058Z
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 b4c03db4-21cc-4f0e-a157-206a12c35c98 · inbound
Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail cites this paper.
Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T02:35:13.250091Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f1d297af-7e3c-427a-8399-a985524f16bf · inbound
Efficient Preference Poisoning Attack on Offline RLHF cites this paper.
Efficient Preference Poisoning Attack on Offline RLHF Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
Reference 105
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-09T05:50:27.193270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 162dcb79-ef93-4d05-96a1-fbdb404cc692 · inbound
Position: Good Embodied Reward Models Need Bad Behavior Data cites this paper.
Position: Good Embodied Reward Models Need Bad Behavior Data Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T17:22:25.030743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 96684f18-60ad-4f5b-9462-9273155a96e9 · inbound
CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning cites this paper.
CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T12:23:58.275386Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 292b40bf-10d7-4ed0-b31c-615353f89f60 · inbound
Towards General Language-Conditioned Latent Safety Filters cites this paper.
Towards General Language-Conditioned Latent Safety Filters Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
Reference 218
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T00:49:36.689172Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.