Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Language Models are Few-Shot Butlers
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2104.07972.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:23:34.979110Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T08:57:22.381225Z
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 923a72de-6f71-463e-a2f1-d75782301fc8 · inbound
VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models cites this paper.
VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models Language Models are Few-Shot Butlers
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T08:57:22.382880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 33462200-789e-4de1-9aa4-a1124f8526a1 · inbound
Embodied CoT Distillation From LLM To Off-the-shelf Agents cites this paper.
Embodied CoT Distillation From LLM To Off-the-shelf Agents Language Models are Few-Shot Butlers
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:56:14.666636Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af2e81d4-0d99-4897-ae59-caa088c1aef8 · inbound
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents cites this paper.
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents Language Models are Few-Shot Butlers
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:23:34.979110Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.