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Paper Citation Record · LEDGER

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach

As of 9 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2507.00601.

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

pith.paper-citation-record.v1
2507.00601 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:17:25.713019Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:08:05.021116Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:08:05.203592Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact4
  • verified fuzzy15
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0e87cfb-778f-4738-9cc7-07aa179b4dab · outbound

This paper cites Fine-tuning large language models for improved health communication in low-resource languages.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Fine-tuning large language models for improved health communication in low-resource languages

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:31.641828Z

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.

source=pdf_text observed=2026-08-06T21:17:22.462937Z digest=sha256:d4de7cde809aaf2e2cdbe4b58c4869d4d0eea89ee42a655483ad542e83514ed7

Observation 38c1152f-4200-45d4-a7bd-cedaecc839b8 · outbound

This paper cites Fine-tuning large neural language models for biomedical natural language processing.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Fine-tuning large neural language models for biomedical natural language processing

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:31.423489Z

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.

source=pdf_text observed=2026-08-06T21:17:22.642270Z digest=sha256:05022ea1e349f294153a57cac4aa01f4fc5f5c3047a4d69478bec2e7cb9b0028

Observation 9f35b6f1-07bb-4830-b423-9a0469b37a05 · outbound

This paper cites Towards low-resource languages machine translation: A language-specific fine-tuning with LoRA for specialized large language models.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Towards low-resource languages machine translation: A language-specific fine-tuning with LoRA for specialized large language models

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:31.204901Z

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.

source=pdf_text observed=2026-08-06T21:17:22.757306Z digest=sha256:4b267feb73058b91c8d6f13d650929caaaae2ca7a22a830b02f065e3af18a7c0

Observation 698b2ce2-65b0-4420-b97e-339651761649 · outbound

This paper cites an unresolved cited work.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:17:30.995282Z

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.

source=pdf_text observed=2026-08-06T21:17:22.911517Z digest=sha256:f95d8eba0964316d1a5b8ade2b5d296f1dff11299663f4f4c1750e350a3f6c79

Observation 7cc1bc66-2c9d-4e40-8f21-cd0e2fe260cf · outbound

This paper cites an unresolved cited work.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:17:30.814822Z

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.

source=pdf_text observed=2026-08-06T21:17:23.029784Z digest=sha256:6693019889297f1a9c88df21aa94463b75e72b0ab518bed840f9782c3a5cf148

Observation 1447a2fe-533e-4e27-92c3-7a334d2318f3 · outbound

This paper cites Optimizing translation for low-resource languages: Efficient fine-tuning with custom prompt engineering in large language models.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Optimizing translation for low-resource languages: Efficient fine-tuning with custom prompt engineering in large language models

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:30.628386Z

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.

source=pdf_text observed=2026-08-06T21:17:23.134945Z digest=sha256:10bc66d924f52af74f987c9448c4b236a4026b0114a8bdd2a01831e3e753e7e1

Observation e106b73b-ea47-42f7-92fd-0ca0b5df5a87 · outbound

This paper cites Comparative Analysis of Different Efficient Fine Tuning Methods of Large Language Models (LLMs) in Low-Resource Setting.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Comparative Analysis of Different Efficient Fine Tuning Methods of Large Language Models (LLMs) in Low-Resource Setting

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T21:17:23.273943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:17:23.273943Z digest=sha256:bf3c75d261567ee6bb1a91918bd057d2dce43c435446722a22f14f8bdbf0a15c

Observation f79ac9c8-2600-48f2-ac88-7a4a265a2d2d · outbound

This paper cites adaptmllm: Fine-tuning multilingual language models on low-resource languages with integrated llm playgrounds.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach adaptmllm: Fine-tuning multilingual language models on low-resource languages with integrated llm playgrounds

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:30.329530Z

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.

source=pdf_text observed=2026-08-06T21:17:23.404839Z digest=sha256:bc2cbeecf59f44a869a7b4a8abb68875a99bf96a1dcd04f73c06eed92349fa7b

Observation 3651a16e-671e-41c6-b231-7794fbf44838 · outbound

This paper cites Generalizable and Stable Finetuning of Pretrained Language Models on Low-Resource Texts.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Generalizable and Stable Finetuning of Pretrained Language Models on Low-Resource Texts

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:17:27.012461Z

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.

source=pdf_text observed=2026-08-06T21:17:23.554678Z digest=sha256:1da526bc73c00fc0f5f1482e0b9ebba7fcff5213983f0862850dfe8f63d35f95

Observation a781681b-9350-44cc-8f75-b5b99235ed04 · outbound

This paper cites Structured Memory Mechanisms for Stable Context Representation in Large Language Models.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Structured Memory Mechanisms for Stable Context Representation in Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T21:17:23.763881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:17:23.763881Z digest=sha256:560469a7219ef12f15158c80fd9e356c2f558964e1f6ce931c48067a598d95bc

Observation b0c29aff-011a-4911-92f1-fc9497bc81bd · outbound

This paper cites Distilling Semantic Knowledge via Multi-Level Alignment in TinyBERT-Based Language Models,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Distilling Semantic Knowledge via Multi-Level Alignment in TinyBERT-Based Language Models,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:30.030867Z

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.

source=pdf_text observed=2026-08-06T21:17:23.880605Z digest=sha256:5fcf2f16bfb0791e7a5b84939fb98edd2e804472976f6cefd99c580c98338705

Observation 1f113ed2-b976-4660-ad2f-942e0c19d4aa · outbound

This paper cites Unified Instruction Encoding and Gradient Coordination for Multi-Task Language Models,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Unified Instruction Encoding and Gradient Coordination for Multi-Task Language Models,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:29.734336Z

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.

source=pdf_text observed=2026-08-06T21:17:24.029712Z digest=sha256:9a8897c7b5cb95d2b84b9520a9307c3aca2b8a51bcc44090f6aa49674627ca4a

Observation 9631bb77-5098-4159-aef6-798631597e85 · outbound

This paper cites Perception-Guided Structural Framework for Large Language Model Design,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Perception-Guided Structural Framework for Large Language Model Design,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:29.538133Z

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.

source=pdf_text observed=2026-08-06T21:17:24.186580Z digest=sha256:4294205311aa3f173c1a01f64323cf76a36c1797a61b0f4a5b1fb1a44ced5292

Observation 1945fd1e-3732-40a8-8cb2-674213e788a8 · outbound

This paper cites A Deep Learning-Based Predictive Framework for Backend Latency Using AI-Augmented Structured Modeling,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach A Deep Learning-Based Predictive Framework for Backend Latency Using AI-Augmented Structured Modeling,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:29.270528Z

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.

source=pdf_text observed=2026-08-06T21:17:24.382241Z digest=sha256:66fab0f038a2b7d6cf471f52bdb1e068304bf29b7d7d969a8c7d4a427ae36fe9

Observation a244c276-e8f1-4dcc-9971-db88c2edf1df · outbound

This paper cites Deep Graph Modeling for Performance Risk Detection in Structured Data Queries,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Deep Graph Modeling for Performance Risk Detection in Structured Data Queries,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:28.934752Z

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.

source=pdf_text observed=2026-08-06T21:17:24.523450Z digest=sha256:947ddffb149f2f4f4b0b5d55370399b9f3cfaa6f2f5bc17fb6e871704b72ecab

Observation a4b1faf2-a490-47d3-a20f-59adbcbd27c4 · outbound

This paper cites Context-Aligned and Evidence-Based Detection of Hallucinations in Large Language Model Outputs,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Context-Aligned and Evidence-Based Detection of Hallucinations in Large Language Model Outputs,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:28.614752Z

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.

source=pdf_text observed=2026-08-06T21:17:24.707085Z digest=sha256:d5c25f73caae8ce947430b6941ce1efd085cf76c734a2363f24ace240d490a73

Observation 88034551-d588-4f18-a30a-a91d35b9ee2a · outbound

This paper cites A Deep Q-Network Approach to Intelligent Cache Management in Dynamic Backend Environments,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach A Deep Q-Network Approach to Intelligent Cache Management in Dynamic Backend Environments,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:28.321856Z

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.

source=pdf_text observed=2026-08-06T21:17:24.795397Z digest=sha256:8fdb90159e0181df706b682640403406546316952078149a6e98bf78ac95ee2d

Observation 71067943-0ada-48ed-a2a1-44485f76354e · outbound

This paper cites Graph Neural Network-Based Collaborative Perception for Adaptive Scheduling in Distributed Systems.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Graph Neural Network-Based Collaborative Perception for Adaptive Scheduling in Distributed Systems

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T21:17:24.914874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:17:24.914874Z digest=sha256:49acb2f6b3c367c508b7ad34be83b2777263cfb9b5f58740b5374808090b6fd9

Observation 76defd86-25b5-486f-aa35-8eae466ba834 · outbound

This paper cites Self-Attention-Based Modeling of Multi-Source Metrics for Performance Trend Prediction in Cloud Systems,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Self-Attention-Based Modeling of Multi-Source Metrics for Performance Trend Prediction in Cloud Systems,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:28.046918Z

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.

source=pdf_text observed=2026-08-06T21:17:25.124752Z digest=sha256:b232c3e550a195c275fa9a28f0f9725eacd7fccfed396d5993b57405f5fbcdbf

Observation d5ed12f6-0215-48c5-900c-235dc9263a76 · outbound

This paper cites A Meta-Learning Framework for Cross-Service Elastic Scaling in Cloud Environments,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach A Meta-Learning Framework for Cross-Service Elastic Scaling in Cloud Environments,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:27.639799Z

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.

source=pdf_text observed=2026-08-06T21:17:25.258604Z digest=sha256:0b5864717e22b553bdda5a99e34197cfa6ddf01caf6d651e6093fcd7a4e7cd2b

Observation 01a38c7a-89f4-4f56-b388-10bb8d8c7f20 · outbound

This paper cites Anomaly Detection in Microservice Environments via Conditional Multiscale GANs and Adaptive Temporal Autoencoders,.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Anomaly Detection in Microservice Environments via Conditional Multiscale GANs and Adaptive Temporal Autoencoders,

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T21:17:25.334047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:17:25.334047Z digest=sha256:0739161b68dad389f64790bdfd5a64ac661f0ae58fa25153250eb4e89a430d3c

Observation ad017e39-49ea-4a24-baa6-204af76f126a · outbound

This paper cites BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:17:26.584797Z

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.

source=pdf_text observed=2026-08-06T21:17:25.484886Z digest=sha256:eca4589242c37d9dcd490149398b9bf6cebba2d5859f992c651fdd71ea7b415c

Observation 065f1fc3-90e3-4473-a586-e54f975e8533 · outbound

This paper cites Sentiment analysis using XLM-R transformer and zero-shot transfer learning on resource-poor Indian language.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach Sentiment analysis using XLM-R transformer and zero-shot transfer learning on resource-poor Indian language

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:17:27.364990Z

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.

source=pdf_text observed=2026-08-06T21:17:25.574846Z digest=sha256:815bdc1dcb6fd37d7ada43bcc1a25902fc9da3ae5817c061a340b3b2ea5a7e6f

Observation cb7fd4be-46b1-48eb-8607-b5c7f917617d · outbound

This paper cites InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:17:26.157034Z

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.

source=pdf_text observed=2026-08-06T21:17:25.653141Z digest=sha256:d9c5cd8e2b2029d91f96932b1ba62675fdfd16a8ef202350b6b58bb0967d6c79

Observation 0449e703-7b86-4366-849e-411b21bf5c42 · outbound

This paper cites VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation.

Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:17:25.938168Z

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.

source=pdf_text observed=2026-08-06T21:17:25.713019Z digest=sha256:5601094afccfd90be66229022828f67963dd6f423ad4d5817bd632731f68c052

Pith citing papers

Observation dc15aae4-b1fd-43b1-9740-c33b5835fd45 · inbound

Collaborative Evolution of Intelligent Agents in Large-Scale Microservice Systems cites this paper.

Collaborative Evolution of Intelligent Agents in Large-Scale Microservice Systems Transferable Modeling Strategies for Low-Resource LLM Tasks: A Prompt and Alignment-Based Approach

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:08:05.208151Z

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.

source=pdf_text observed=2026-08-05T15:08:05.021116Z digest=sha256:377f0ae01fdf6e49d16f71cf6ee8a20157614b4209180b0dd79aa11ecae88ec6