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Paper Citation Record · LEDGER

TAPO: Task-Referenced Adaptation for Prompt Optimization

As of 12 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.06689.

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

pith.paper-citation-record.v1
2501.06689 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:57:57.351798Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy9
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f023041-1a13-40cf-9f97-8512b471c7d3 · outbound

This paper cites A Survey of Large Language Models.

TAPO: Task-Referenced Adaptation for Prompt Optimization A Survey of Large Language Models

Reference 1

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source=pdf_text observed=2026-08-10T20:57:57.204584Z digest=sha256:987585809a327fb12d9e582ef03994372720500f1e141c4819becaed3dc36dd9

Observation c8a47a52-bd68-49dc-bec2-5375490bf66d · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

TAPO: Task-Referenced Adaptation for Prompt Optimization Large Language Models Are Human-Level Prompt Engineers

Reference 2

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source=pdf_text observed=2026-08-10T20:57:57.209794Z digest=sha256:7da531cbcb0ee61260104f1a9e3818530598fbb5ba27c0e1a36695d8add14a0f

Observation db62fc0d-8277-4df0-928e-0e4ee1865dc4 · outbound

This paper cites TEMPERA: Test-Time Prompting via Reinforcement Learning.

TAPO: Task-Referenced Adaptation for Prompt Optimization TEMPERA: Test-Time Prompting via Reinforcement Learning

Reference 3

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source=pdf_text observed=2026-08-10T20:57:57.214519Z digest=sha256:545299c06ee2fcb8b92052c2cc8aff5c74a7fbc9344274232ea39575879b45c4

Observation ce491cec-002a-4be4-9849-791a67f5aeb8 · outbound

This paper cites Selective Annotation Makes Language Models Better Few-Shot Learners.

TAPO: Task-Referenced Adaptation for Prompt Optimization Selective Annotation Makes Language Models Better Few-Shot Learners

Reference 4

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source=pdf_text observed=2026-08-10T20:57:57.219130Z digest=sha256:9c8b07421edb971d1df10d1f9a41b54b4ebb5a2c94b591b74d67117bfc685583

Observation a5015de3-dd5c-46fa-924a-474c8af93ccd · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

TAPO: Task-Referenced Adaptation for Prompt Optimization Automatic Chain of Thought Prompting in Large Language Models

Reference 5

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source=pdf_text observed=2026-08-10T20:57:57.223686Z digest=sha256:91b00ef858c77952a2f87650cf39ed05385f5288ae0de132b87d52a2d476b3cb

Observation 7dbaf967-916d-481c-bd3a-7dc686e5df20 · outbound

This paper cites Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

TAPO: Task-Referenced Adaptation for Prompt Optimization Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution

Reference 6

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source=pdf_text observed=2026-08-10T20:57:57.228068Z digest=sha256:e61beff0b457d8fd5bab15a927c5aa87168ecad8396883819873d83aff9d826e

Observation 3b9de0e8-0556-425d-a29f-0dc540e73cbe · outbound

This paper cites Eliciting Human Preferences with Language Models.

TAPO: Task-Referenced Adaptation for Prompt Optimization Eliciting Human Preferences with Language Models

Reference 7

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source=pdf_text observed=2026-08-10T20:57:57.232588Z digest=sha256:2ad1c4036aadababdc793c5843d2ee1296a884c0e67e4fabc71a0a92a8b00c2e

Observation cdab32b4-89be-4f94-a7ed-5b2fe2c5ec82 · outbound

This paper cites Machine Translation with Large Language Models: Prompt Engineering for Persian, English, and Russian Directions.

TAPO: Task-Referenced Adaptation for Prompt Optimization Machine Translation with Large Language Models: Prompt Engineering for Persian, English, and Russian Directions

Reference 8

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.236585Z digest=sha256:1457c7df30b632c128d945942f32137ed7920fbb1c6b4b0cc803180eb7123f74

Observation bed22a47-5f96-4ab6-9e0a-db937800109c · outbound

This paper cites Learning to solve arithmetic word problems with verb categorization,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Learning to solve arithmetic word problems with verb categorization,

Reference 9

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.240723Z digest=sha256:cb5ad602798ea2912aeffad122eb0ce3040b21a66db69bf8eb494c26be5680c0

Observation e0585452-8361-4a80-990e-73c4e9183963 · outbound

This paper cites Solving General Arithmetic Word Problems.

TAPO: Task-Referenced Adaptation for Prompt Optimization Solving General Arithmetic Word Problems

Reference 10

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source=pdf_text observed=2026-08-10T20:57:57.244666Z digest=sha256:19ec3cadee4d0df68e10555eeb2ec22c724f49a458ce661ef037f2ffb2d8b7c4

Observation 4d3068c4-0f41-48ba-8e69-1626d8eedadd · outbound

This paper cites Parsing algebraic word problems into equations,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Parsing algebraic word problems into equations,

Reference 11

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.248843Z digest=sha256:24fee1aa076ec0ed49a8cb813ac1980fcd4148d16956a3af591e8388c7495940

Observation 786ec855-78fc-49bf-8966-0defde8d8956 · outbound

This paper cites Are NLP Models really able to Solve Simple Math Word Problems?.

TAPO: Task-Referenced Adaptation for Prompt Optimization Are NLP Models really able to Solve Simple Math Word Problems?

Reference 12

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source=pdf_text observed=2026-08-10T20:57:57.253032Z digest=sha256:975939b1831803b236141bf14c6af2a7ed729376cf299d1366f67c8f86e354dc

Observation f1ab0ca7-4e95-4206-a6a9-7073807e8e8a · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

TAPO: Task-Referenced Adaptation for Prompt Optimization Training Verifiers to Solve Math Word Problems

Reference 13

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source=pdf_text observed=2026-08-10T20:57:57.257834Z digest=sha256:11322d7ad58e272523c3bfec26888d6c02bc3cf0f9ae64dee8e403925757b486

Observation 0df76838-29dd-462a-9686-812e9eef82e6 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

TAPO: Task-Referenced Adaptation for Prompt Optimization Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 14

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source=pdf_text observed=2026-08-10T20:57:57.261868Z digest=sha256:c8b155fd462dffa914fcd1bea836e51284842e12c777697c09f83d033c7225c1

Observation 9f618c1d-46b5-4f77-9c70-c9f6d7af3caf · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Chain-of-thought prompting elicits reasoning in large language models,

Reference 15

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source=pdf_text observed=2026-08-10T20:57:57.265588Z digest=sha256:752d8cade921f594854a892e2daefdc95e7defe0cc5bf65b9713c57d912201a3

Observation 48bd574a-f133-46a3-a46f-b376c212ff4a · outbound

This paper cites Prompt Engineering a Prompt Engineer.

TAPO: Task-Referenced Adaptation for Prompt Optimization Prompt Engineering a Prompt Engineer

Reference 16

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source=pdf_text observed=2026-08-10T20:57:57.269171Z digest=sha256:8c1565bcb96639b0bc40b0718c11fd28ca78400b5244cbf22cce9d7696867840

Observation e86a117e-311d-4541-98d8-2363c75d15d9 · outbound

This paper cites Gpt-3.5 turbo model documentation,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Gpt-3.5 turbo model documentation,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.273042Z digest=sha256:42306c56be9a0d09bb493bbc023966721793e164d28a9a5500c21b30d513dfee

Observation 2b8c105a-0ff5-45c0-bdab-efbbc9bef7b3 · outbound

This paper cites GPT-4o System Card.

TAPO: Task-Referenced Adaptation for Prompt Optimization GPT-4o System Card

Reference 18

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source=pdf_text observed=2026-08-10T20:57:57.276383Z digest=sha256:c7fc7f7392182515e885af70a3de735506d3aad0ef4bfaaff9300fb0bc85c640

Observation 5ea3741b-e87c-4291-8d84-3a1445c427f5 · outbound

This paper cites The Llama 3 Herd of Models.

TAPO: Task-Referenced Adaptation for Prompt Optimization The Llama 3 Herd of Models

Reference 19

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source=pdf_text observed=2026-08-10T20:57:57.280108Z digest=sha256:172a84c9513fe0f791ecce486a0a762585243b72b626860c50934480c3c0ef97

Observation 438feaf7-c3a7-4a58-a5fa-27e19e30d9c5 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

TAPO: Task-Referenced Adaptation for Prompt Optimization Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 20

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source=pdf_text observed=2026-08-10T20:57:57.283958Z digest=sha256:bf4235835d3fcb9db824b3f61bea44c990bda02a4eead364f9c2ccc7e99da9a0

Observation 930562fb-262f-4fe2-9576-9fe6b792d7e0 · outbound

This paper cites Language models are unsupervised multitask learners,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Language models are unsupervised multitask learners,

Reference 21

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source=pdf_text observed=2026-08-10T20:57:57.287798Z digest=sha256:d8ee7a8acd4548c611d8ff0c16752e2197254ca02c8d0d6d8bf6bd44bcddb6ab

Observation a9e0e4b7-baae-4226-9d20-5b52840e2e83 · outbound

This paper cites Agentir: 1st workshop on agent-based information retrieval,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Agentir: 1st workshop on agent-based information retrieval,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.291646Z digest=sha256:d46a7219a69bf0e27e93aeeaac38e05e6de05e4ae4c51520f22240691b04533c

Observation 1763a815-8c84-44a2-81bf-285f7fcb0fe9 · outbound

This paper cites Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLM.

TAPO: Task-Referenced Adaptation for Prompt Optimization Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLM

Reference 23

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source=pdf_text observed=2026-08-10T20:57:57.295476Z digest=sha256:397fb96588b9695f5c089b1307905c6f676800d2358579e85dd60d66313001b7

Observation 389c37ed-4bab-477c-927d-682f32cbeb24 · outbound

This paper cites Bridging relevance and reasoning: Rationale distillation in retrieval-augmented generation,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Bridging relevance and reasoning: Rationale distillation in retrieval-augmented generation,

Reference 24

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source=pdf_text observed=2026-08-10T20:57:57.299393Z digest=sha256:85b54fd3491ccc38fe7304b749a85f4f7e83593c50524eb22f8b54f49ebdf0f9

Observation ccfd6b27-d8c3-4228-ae77-6c1767a7117e · outbound

This paper cites G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models.

TAPO: Task-Referenced Adaptation for Prompt Optimization G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models

Reference 25

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source=pdf_text observed=2026-08-10T20:57:57.303315Z digest=sha256:25ea78fc55371c2f10f284e61fd5c8d5a3054afc8ab4ede1a30c8b6b9f32b204

Observation bc09719e-d048-4440-9ccb-1908200242bd · outbound

This paper cites SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval.

TAPO: Task-Referenced Adaptation for Prompt Optimization SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval

Reference 26

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source=pdf_text observed=2026-08-10T20:57:57.307405Z digest=sha256:14775b77748435fb158fbe4a1d269f39af36a31a0ca428785381af690a0ebfdb

Observation 1d934965-6c4f-4ad8-a2d9-08fe42313ac8 · outbound

This paper cites MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion.

TAPO: Task-Referenced Adaptation for Prompt Optimization MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion

Reference 27

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source=pdf_text observed=2026-08-10T20:57:57.311452Z digest=sha256:5a478f7e3dad82ecf5c800543f2be0983e8f33f2a9d44843cead8c08db111dec

Observation 0b4af15d-f18e-4548-b6fa-8d6ef921e42e · outbound

This paper cites When moe meets llms: Parameter efficient fine-tuning for multi-task medical applications,.

TAPO: Task-Referenced Adaptation for Prompt Optimization When moe meets llms: Parameter efficient fine-tuning for multi-task medical applications,

Reference 28

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.315684Z digest=sha256:a739180e00f84884e5d5b97b0723ae9410f71f9090920f07f76726068fcc7e92

Observation 5bf60ac7-6766-4ef2-ab7a-89867eb8baae · outbound

This paper cites Llm-esr: Large language models enhancement for long-tailed sequential recommendation,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Llm-esr: Large language models enhancement for long-tailed sequential recommendation,

Reference 29

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raw_fallback, observed 2026-08-10T20:57:57.984358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.319691Z digest=sha256:b4a4ddb33a8ed8a059a24fda7324c8548af2f0097dc32cb8ee9341420ed32aa5

Observation 2c29968a-5eae-4828-90a6-26bbadba1325 · outbound

This paper cites Hamur: Hyper adapter for multi-domain recommendation,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Hamur: Hyper adapter for multi-domain recommendation,

Reference 30

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raw_fallback, observed 2026-08-10T20:57:57.971827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.323852Z digest=sha256:d647b48c277e9592754efff76fd76a6e41f9500105991d7814e256e706a59e49

Observation 1157c6b6-1827-454e-a222-8a3fe8c5164b · outbound

This paper cites Hierrec: Scenario-aware hierarchical modeling for multi-scenario recommendations,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Hierrec: Scenario-aware hierarchical modeling for multi-scenario recommendations,

Reference 31

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raw_fallback, observed 2026-08-10T20:57:57.959671Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.327719Z digest=sha256:ae40b43836be913f69c9f857ff83861b9ca2a283d5fe2ea89983510fd37e9140

Observation 55ad6b5a-3c81-4e23-b1c6-a38b55424f89 · outbound

This paper cites D3: A methodological exploration of domain division, modeling, and balance in multi-domain recommendations,.

TAPO: Task-Referenced Adaptation for Prompt Optimization D3: A methodological exploration of domain division, modeling, and balance in multi-domain recommendations,

Reference 32

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raw_fallback, observed 2026-08-10T20:57:57.946284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:57:57.331530Z digest=sha256:44099d95a234bbe01250e0feb176903096ce4cb99f3eb35500f949b99dedc60b

Observation 5c93207a-a107-43aa-b548-b6075042177b · outbound

This paper cites Scenario-wise rec: A multi-scenario recommendation benchmark,.

TAPO: Task-Referenced Adaptation for Prompt Optimization Scenario-wise rec: A multi-scenario recommendation benchmark,

Reference 33

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source=pdf_text observed=2026-08-10T20:57:57.335312Z digest=sha256:a3cebb8d11e5cdb9d994a4186d0d2a9281d0d879f10b9ee70b1c4600fe42feee

Observation 93b1f11d-d6f7-415c-9b9a-7d7733184e1e · outbound

This paper cites Large Language Model Enhanced Recommender Systems: A Survey.

TAPO: Task-Referenced Adaptation for Prompt Optimization Large Language Model Enhanced Recommender Systems: A Survey

Reference 34

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source=pdf_text observed=2026-08-10T20:57:57.339073Z digest=sha256:b46fd283fa58e7037f6a07cc8152b4412010fef6643014c20d6e84b38be1df63

Observation c4805968-4bf5-4b99-887c-d574c4096d86 · outbound

This paper cites LLM-Powered User Simulator for Recommender System.

TAPO: Task-Referenced Adaptation for Prompt Optimization LLM-Powered User Simulator for Recommender System

Reference 35

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source=pdf_text observed=2026-08-10T20:57:57.343470Z digest=sha256:2e7796810d01a1a148e8ae98951dfcb86de521cb22939bf7dc6dd7eeef508c14

Observation 578c3166-080e-4c40-b478-5d9a0c485158 · outbound

This paper cites RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning.

TAPO: Task-Referenced Adaptation for Prompt Optimization RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

Reference 36

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source=pdf_text observed=2026-08-10T20:57:57.347711Z digest=sha256:b070b51ff9a30aabf18a28c37d186c61b5e11538bee5fa62809e284e38f1c620

Observation 13e9e4b2-5e41-4ea5-a9b3-af2e065d6df2 · outbound

This paper cites Large Language Models to Enhance Bayesian Optimization.

TAPO: Task-Referenced Adaptation for Prompt Optimization Large Language Models to Enhance Bayesian Optimization

Reference 37

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unresolved
no resolver link, observed 2026-08-10T20:57:57.351798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:57:57.351798Z digest=sha256:bc08685a0d5985995f7a6f5835eba13bf6e46f2807de174278d30e9c730f01e1

Pith citing papers

No inbound Pith citation observations are available.