Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2108.13161.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:45:09.556865Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T20:53:17.678465Z
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 7d45062b-dc93-4694-8816-6a33fd037023 · inbound
OPT: Open Pre-trained Transformer Language Models cites this paper.
OPT: Open Pre-trained Transformer Language Models Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 197
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T20:53:17.680469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c80ca561-98e4-4226-9a24-d2c2b986d89f · inbound
PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks cites this paper.
PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:29:54.172730Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b91aba6-bc72-454f-bdcf-a0e35012da68 · inbound
Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages cites this paper.
Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T18:18:29.491688Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30e07c84-6747-4cd2-b80b-b4f295628d48 · inbound
Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization cites this paper.
Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:43:51.855934Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7b332df-68e6-475f-8393-4b667bdf52de · inbound
Parameter-Efficient Fine-Tuning for Foundation Models cites this paper.
Parameter-Efficient Fine-Tuning for Foundation Models Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 138
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:38:03.276027Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c14d253-c6d7-41c8-9d08-c0b00838c9fa · inbound
Advancing Uto-Aztecan Language Technologies: A Case Study on the Endangered Comanche Language cites this paper.
Advancing Uto-Aztecan Language Technologies: A Case Study on the Endangered Comanche Language Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:45:09.556865Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ae86476-2721-4e16-bf83-7a0dda9372ff · inbound
Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings cites this paper.
Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:15:42.173153Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 504efef7-b724-427a-bff6-482a1560c6a0 · inbound
Relic: Enhancing Reward Model Generalization for Low-Resource Indic Languages with Few-Shot Examples cites this paper.
Relic: Enhancing Reward Model Generalization for Low-Resource Indic Languages with Few-Shot Examples Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:32:11.919187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb52b242-37c6-42c9-8349-e24c482fe024 · inbound
ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling cites this paper.
ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Reference 71
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:10:45.163317Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.