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Paper Citation Record · LEDGER

PPT: Pre-trained Prompt Tuning for Few-shot Learning

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2109.04332.

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

pith.paper-citation-record.v1
2109.04332 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:20:32.469793Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:29:51.163212Z

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 754c65ba-4863-4b82-ba55-02b056f8a380 · inbound

Towards Expert-Level Medical Question Answering with Large Language Models cites this paper.

Towards Expert-Level Medical Question Answering with Large Language Models PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 74

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:32:33.563953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-24T04:32:33.271634Z digest=sha256:a194d36ea5cdefb231fb221a5579b5c3b2296e4c85093334ca4c43912b690023

Observation 4a05abdf-034d-4bee-9039-8037ad9f7cac · inbound

Hymba: A Hybrid-head Architecture for Small Language Models cites this paper.

Hymba: A Hybrid-head Architecture for Small Language Models PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T16:20:32.469793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:20:32.469793Z digest=sha256:34f1d3d1ac76f1e1b1a1673546447365b94582e498ea01c58344805febda5cc7

Observation 8ad4ec56-45e5-40a5-a2a5-9f92d00d59bd · inbound

Instance-Aware Graph Prompt Learning cites this paper.

Instance-Aware Graph Prompt Learning PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T11:56:36.696323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.696323Z digest=sha256:57c5e074141b073dd667e5fc56e03704d7ae3f4b50ac744cfa58ad0314718ac1

Observation a17d2bad-5925-44c8-9db0-10da4307fe46 · inbound

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis cites this paper.

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T21:06:56.966307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:06:56.966307Z digest=sha256:425fc9f357e8524ae755844aca5b1217f82316038479cdb6aa6fad405109269a

Observation 517d6aa6-979a-4842-a0e5-e3e409206b80 · inbound

CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets cites this paper.

CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T21:57:41.786939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:57:41.786939Z digest=sha256:f3f6cfb8611a93244e11d3a7706f125710aab482e6d88769e9c91b50828afe22

Observation 34e33a1f-fbde-47be-8efa-2324bd0c6434 · inbound

ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono cites this paper.

ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T21:51:12.124752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:51:12.124752Z digest=sha256:33437291ab2a411c37c4f47d26ac289f98ac74bb44fc35fd1519d7b3a4e36e96

Observation e5c565ec-9020-4a27-adab-2919c2d7838d · inbound

MPLinker: Multi-template Prompt-tuning with Adversarial Training for Issue-commit Link Recovery cites this paper.

MPLinker: Multi-template Prompt-tuning with Adversarial Training for Issue-commit Link Recovery PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-09T21:39:57.652312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T21:39:57.652312Z digest=sha256:a9eb8f62f4e611bc3ea9dcc65a7060fe870b78eef2ac33472040bbc9346e96a2

Observation 5889d7bf-c960-4931-a6f9-32273fad0234 · inbound

Towards an AI co-scientist cites this paper.

Towards an AI co-scientist PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 156

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:02:45.012569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-11T13:02:43.571234Z digest=sha256:5f7c653ae895d84266015c17f7b48ff4344fb345c3d2dd6f8fa095818334288a

Observation de659a86-02eb-4d45-882f-efbe05a8f1c7 · inbound

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation cites this paper.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:48:02.268463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:48:02.268463Z digest=sha256:f60d6593a60882df90e004f93b8611ef76a42be4e6625868e696ef440000e7da

Observation 5ba7897d-c4d9-4803-a810-f6d225f73e52 · inbound

Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering cites this paper.

Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T12:02:10.520637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:02:10.520637Z digest=sha256:f4aa56269e5b7ee0158a6bf6f901bb0a9eece94d44d73f98148f5187b65a1923

Observation 06241424-df58-4ad2-b92c-48ca5ff65bd8 · inbound

Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectives cites this paper.

Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectives PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-07T04:46:04.414376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:46:04.414376Z digest=sha256:cb2ef2d38e068c6caa9d3079694af702cc469bf6cf93e0e6018755984db2ae74

Observation 298261b1-61cc-4c71-a3eb-a464b76f3c39 · inbound

Mettle: Meta-Token Learning for Memory-Efficient Audio-Visual Adaptation cites this paper.

Mettle: Meta-Token Learning for Memory-Efficient Audio-Visual Adaptation PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T21:52:05.682604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:52:05.682604Z digest=sha256:41bace1cc1844a10785cbbc54d1168f3726c8853faa6e1c512dff4885909302e

Observation ded21617-762f-4eab-9429-142acbf17f72 · inbound

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning cites this paper.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:55:28.942688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:55:28.942688Z digest=sha256:0289b221114d86b62a9c7f1199101bb4fa9a68b18b02a87befe057e54ef2988f

Observation 8c7d8920-f901-4044-90c3-c13f23460a4d · inbound

Graph Topology Information Enhanced Heterogeneous Graph Representation Learning cites this paper.

Graph Topology Information Enhanced Heterogeneous Graph Representation Learning PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:55:51.308913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T19:27:45.961277Z digest=sha256:3d4f1c6668a80a82ac5e160557e219ef2807b6a6c0c3a7886d110c128a59def2

Observation 1ed903a1-754a-4d13-b64f-95c874d4b702 · inbound

Structure Before Collapse: Transient semantic geometry in next-token prediction cites this paper.

Structure Before Collapse: Transient semantic geometry in next-token prediction PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 177

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:29:51.164630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-26T05:14:07.208255Z digest=sha256:e7eb178e4c62869914b8ebb7d2d01f350e3c11f757ecc9d2931c6147393183b8