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Paper Citation Record · LEDGER

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter

As of 8 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2607.28657.

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

pith.paper-citation-record.v1
2607.28657 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:49:52.581552Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

56 of 56 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved55
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f111dee-e7cd-4dfc-90fe-12c540238899 · outbound

This paper cites Brown, B.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Brown, B

Reference 1

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source=pdf_text observed=2026-08-03T00:49:52.462005Z digest=sha256:3c8da68ecc236ee2ad9d153e1cd1a07eea1b17a8e28bd31813f85bf980006cc9

Observation a3d90d2d-39a8-4f1f-95e9-d59708486ceb · outbound

This paper cites Emergent Abilities of Large Language Models.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Emergent Abilities of Large Language Models

Reference 2

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source=pdf_text observed=2026-08-03T00:49:52.464923Z digest=sha256:29968289f517a80d02665d2aebeafdedebb1d94a7b13394ca69017a69740faf2

Observation 292d3957-50e3-4db9-95e4-61ac2a39d699 · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 3

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source=pdf_text observed=2026-08-03T00:49:52.467360Z digest=sha256:7f13334185455cae34cc10c678b774d17af68f865f2b1aafe7db80344770b563

Observation 93598914-5163-4410-9892-d806443d48dd · outbound

This paper cites AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Reference 4

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source=pdf_text observed=2026-08-03T00:49:52.469859Z digest=sha256:fdf18477118283acc70653d511476724bccb6536faf55ee5f584daf04360b08a

Observation caa7a5f5-d4a8-4744-aec4-fd7d037f631e · outbound

This paper cites PRewrite: Prompt Rewriting with Reinforcement Learning.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter PRewrite: Prompt Rewriting with Reinforcement Learning

Reference 5

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source=pdf_text observed=2026-08-03T00:49:52.472447Z digest=sha256:b1455b12946d1e6f6b34c4cabc676c482cc36710287b2700d5860f3f19919ee1

Observation 250ba19b-a255-4403-82ff-6016f8960c51 · outbound

This paper cites Schulman, F.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Schulman, F

Reference 6

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source=pdf_text observed=2026-08-03T00:49:52.475137Z digest=sha256:641fd6c49a414b9377f9de55a91e6a2a7f367c50dcf844d90166fb2682e0c533

Observation 1575dde6-b061-4d09-a2f8-153a58d2dcfe · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 7

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source=pdf_text observed=2026-08-03T00:49:52.479730Z digest=sha256:e21852c9d4b2f50e474a6897cbf0054ec7a31148d2a8503995ad0d160ae0da0f

Observation 9ab5638e-9273-44e8-9d64-74b499e839f5 · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-03T00:49:52.482149Z digest=sha256:9c0d4375121aac7d4773bfddcedb6764c78154608b2680e10804f01eca82aed1

Observation e21001d9-7e78-4e41-85a2-61c796840764 · outbound

This paper cites Christiano, J.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Christiano, J

Reference 9

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source=pdf_text observed=2026-08-03T00:49:52.484421Z digest=sha256:a565f3b6d4725b848b25b4acc44e598268a70e5f1b560435064145005bfee86a

Observation 336b1946-a4ef-40b9-a8db-9b1c39deddbe · outbound

This paper cites Ouyang, J.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Ouyang, J

Reference 10

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source=pdf_text observed=2026-08-03T00:49:52.486621Z digest=sha256:2c2b51f83844b7e26b9a5e2eb27acc445bc15ad312bf98528b6096f7f1467996

Observation 5dd9eb20-06f5-4831-a6c4-defd808a16f2 · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 11

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source=pdf_text observed=2026-08-03T00:49:52.488533Z digest=sha256:129ae1e39f419487a99f6a8c81ac2a985e90425e04211472edf59d9699965252

Observation 7874ecc7-3b70-4869-a235-f08430f34792 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 12

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source=pdf_text observed=2026-08-03T00:49:52.492765Z digest=sha256:22c529d304c9de09854e5b478edb50cd97ad7f1452b5e9e135167417f6d16a04

Observation daf4e6cc-fb88-4162-9137-e3b7fe915ff5 · outbound

This paper cites Boonstra, Prompt engineering, Google 5-Day GenAI Intensive Whitepapers-to-Text, Kaggle, 2025.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Boonstra, Prompt engineering, Google 5-Day GenAI Intensive Whitepapers-to-Text, Kaggle, 2025

Reference 13

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source=pdf_text observed=2026-08-03T00:49:52.495176Z digest=sha256:1464730b40ff6f2b78a48fd4cfb131f60428cf0164b78edd40bb7fa7bf81eb3a

Observation 1a0911f7-f715-44f1-b333-49d07c7fd8a8 · outbound

This paper cites Kojima, S.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Kojima, S

Reference 14

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source=pdf_text observed=2026-08-03T00:49:52.497154Z digest=sha256:d6c96272a8c00da8efd77ab29ab2cd91e1557eab8c2782dc61d07ec4d0031d97

Observation b2819ca2-579c-47ae-92e5-4765787fb171 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 15

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source=pdf_text observed=2026-08-03T00:49:52.501812Z digest=sha256:0ea351ee51db53160f83927709eb446f5649272e99aaa142b1446b1c0517bf80

Observation f6289b19-215e-4577-84af-4791f75d1c82 · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-03T00:49:52.504095Z digest=sha256:3f13d460fec148ead90c22a6a4f610ab89a2b17913a18973ee928b7523025a00

Observation fe670066-7f5a-46f9-9676-5b1cfff8ae2d · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-03T00:49:52.506012Z digest=sha256:74847efbb5381a2f4ce816ebfdcf94248962dcb7e39504e233c665bbbf16d17f

Observation 346c84b4-cdc5-4c9f-a0f2-a062a190aa3e · outbound

This paper cites LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs

Reference 18

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source=pdf_text observed=2026-08-03T00:49:52.507932Z digest=sha256:e0b8d91f4665f7fe5d5ccaca7dc32b7ff0ad49efd226d3dbc9431cc45af1883f

Observation 88792332-ad19-41f1-914a-1e735663add2 · outbound

This paper cites Fernando, D.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Fernando, D

Reference 19

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source=pdf_text observed=2026-08-03T00:49:52.510252Z digest=sha256:365a392d15c26df4ed9bdd9d863932bc32fcda582dc1d8c394fe1f93e15831ff

Observation fd63666d-b1a9-4d40-9be5-c61f682c9f2b · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 20

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source=pdf_text observed=2026-08-03T00:49:52.512047Z digest=sha256:b9562bbc6c9f7407195ecc3ce31da9fc1f1be009ffb0986ab7c0f67f155b9bba

Observation 64e7e7dd-31b7-418d-ad3c-84e42ac3f898 · outbound

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

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter TEMPERA: Test-Time Prompting via Reinforcement Learning

Reference 21

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source=pdf_text observed=2026-08-03T00:49:52.514236Z digest=sha256:ee9a016adef18952f618066f84d29703e6bca606a1e09d6c4c0f8fc13b528835

Observation 32b94fd6-4b89-434a-8ac8-4ede14159297 · outbound

This paper cites PaLM 2 Technical Report.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter PaLM 2 Technical Report

Reference 22

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source=pdf_text observed=2026-08-03T00:49:52.516768Z digest=sha256:6c876ffca5e2be1e99878034055d0d68b2c30a35342306fd681365bea826217d

Observation 656fb0e3-f435-4c10-9575-5d65530ecad9 · outbound

This paper cites Papineni, S.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Papineni, S

Reference 23

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source=pdf_text observed=2026-08-03T00:49:52.519124Z digest=sha256:7616ff346015ef48ba916e3efe6ba1dd920a64bee3921b0559418b722297b9b0

Observation 829f7978-4b23-4159-87c8-08fe1f25179c · outbound

This paper cites Lin, Rouge: A package for automatic evaluation of summaries, in: Text Summarization Branches Out, ACL Workshop, 2004, pp.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Lin, Rouge: A package for automatic evaluation of summaries, in: Text Summarization Branches Out, ACL Workshop, 2004, pp

Reference 24

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source=pdf_text observed=2026-08-03T00:49:52.521129Z digest=sha256:358ba81dca8897f9db45030ce78673131097fa6dd4d7107477cf80d220e49cc0

Observation ec4030fb-9234-4c22-bc2b-5a6a70c88754 · outbound

This paper cites Banerjee, A.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Banerjee, A

Reference 25

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source=pdf_text observed=2026-08-03T00:49:52.523002Z digest=sha256:6c9e5be1d10e68e386bf3f462ddfeb051370be002247a3215cd5af965d7e3861

Observation 144bf247-66e8-4bd6-bd46-7c36d5d81639 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter BERTScore: Evaluating Text Generation with BERT

Reference 26

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source=pdf_text observed=2026-08-03T00:49:52.524908Z digest=sha256:14fdba9277139977dc1936096bbed8601b9517f92a3ff6481852b0a3a35acedb

Observation 3362e275-9db1-4f47-9960-79aab3e22cb0 · outbound

This paper cites Saadany, C.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Saadany, C

Reference 27

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doi, observed 2026-08-03T00:54:14.404024Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-03T00:49:52.527011Z digest=sha256:11ccd015b5edda11b46efed27c75347b5126d76483fcbf7404881dc0bfec8150

Observation 04af8c93-2dfb-49bd-b6f3-70e5467ea5c8 · outbound

This paper cites Zheng, W.-L.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Zheng, W.-L

Reference 28

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source=pdf_text observed=2026-08-03T00:49:52.528996Z digest=sha256:aed852028f4bbaaf72867822c01c966b319a03451a6b5a85fc2dd010aa3aaddf

Observation 5f344532-b2ba-4fdc-819c-caf5bce96933 · outbound

This paper cites A Survey on LLM-as-a-Judge.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter A Survey on LLM-as-a-Judge

Reference 29

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source=pdf_text observed=2026-08-03T00:49:52.531055Z digest=sha256:446f2fa8ae50abe4c9856a45c4e4d901ea7159ee2fe8e768b7ef92e852237446

Observation 096d4154-f654-4927-962b-9a90cae6c0e4 · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-03T00:49:52.533242Z digest=sha256:4e29ca346561e195011b603ba9319bd066b3ca5b16bcb4b045c2ecb04ea584e5

Observation 0c545df8-191c-4914-8a52-62184ac87eb9 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Constitutional AI: Harmlessness from AI Feedback

Reference 31

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source=pdf_text observed=2026-08-03T00:49:52.537681Z digest=sha256:b63f391a9d73d1d04f1098d774f5fb51be0c23de8ffb70920141768365125e9a

Observation 08c64702-2266-42ba-bf97-7f4e2f07663e · outbound

This paper cites Kwiatkowski, J.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Kwiatkowski, J

Reference 32

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source=pdf_text observed=2026-08-03T00:49:52.539497Z digest=sha256:3e0b1fbf397b5ccc8f36e4dbd9ed29a95fa7bfe7beba4a6ea4526317169770f6

Observation 3fafdf54-9be8-4cb9-b6e0-b5462259b1cd · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 33

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source=pdf_text observed=2026-08-03T00:49:52.541413Z digest=sha256:c46e8f9057ac537b6de6d46c23e2d99cc51d19f3daa3da931c4d830fb83cf91d

Observation fe7d1b6e-e8cc-4e8a-8ae4-61c60b3b45c4 · outbound

This paper cites Teaching Machines to Read and Comprehend.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Teaching Machines to Read and Comprehend

Reference 34

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source=pdf_text observed=2026-08-03T00:49:52.543397Z digest=sha256:e90eb2daab40441f97340fdb0bca47058f82cc6129a78898a71625c939a26e7d

Observation a1ff5e75-f462-422e-a48f-fcd539c399b7 · outbound

This paper cites Cachola, K.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Cachola, K

Reference 35

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source=pdf_text observed=2026-08-03T00:49:52.545448Z digest=sha256:f1c14c51f161c1187d47153dafb46a9301e9534591a7b15715504616aaf0104b

Observation 66bab5c6-3660-4482-b8cb-608ec3d04235 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Training Verifiers to Solve Math Word Problems

Reference 36

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source=pdf_text observed=2026-08-03T00:49:52.547540Z digest=sha256:e856c363d3f30d3c0aca97c14fb2cf4e169ee60a88ebabd7d5cca020da296d1e

Observation cfe75c1e-dfe1-4fb1-a333-861a23b6a7e4 · outbound

This paper cites A Survey of Automatic Prompt Engineering: An Optimization Perspective.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter A Survey of Automatic Prompt Engineering: An Optimization Perspective

Reference 37

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source=pdf_text observed=2026-08-03T00:49:52.549569Z digest=sha256:56c7ffdcf0f2b4ef5d3f2181231e6eb93157c71439402a7fe45ccc57446a67df

Observation 498c2d30-3959-489a-8f82-acb039e3654a · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 38

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source=pdf_text observed=2026-08-03T00:49:52.551947Z digest=sha256:9913c8d0866096c38b1c7bec48fa816fb137d9d9066c7efe64dc595258b35b32

Observation 4fb3c044-14ca-4aec-b80f-b968972f813d · outbound

This paper cites The Llama 3 Herd of Models.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter The Llama 3 Herd of Models

Reference 39

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source=pdf_text observed=2026-08-03T00:49:52.554000Z digest=sha256:4e994bf1ca5d1b6b81d2a2c7f0c7e5409ed49ac7635c249aebd3966346999733

Observation 830ce2d5-1efc-4192-a625-b2d5eedcfb7a · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 40

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source=pdf_text observed=2026-08-03T00:49:52.556106Z digest=sha256:f4c76db8e06cb16cc54c32b66461536bc5d3c7e5b7459bb0890ae6befe921c80

Observation addacac7-502e-4bce-ac45-9710b90f11d2 · outbound

This paper cites URL: https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/, meta AI Blog.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter URL: https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/, meta AI Blog

Reference 41

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source=pdf_text observed=2026-08-03T00:49:52.558820Z digest=sha256:96c4a42e339f91b81233befeab575a1c3d76984bdbef530baf7b5b4c5c74144e

Observation a0eea565-bcf0-4e5e-a7b0-6b8f2540e99a · outbound

This paper cites Qwen3 Technical Report.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Qwen3 Technical Report

Reference 42

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source=pdf_text observed=2026-08-03T00:49:52.560677Z digest=sha256:d02739ea3972210499cd4881a1f791e47403141a3c5c0c5bc2fa1c4c0da10805

Observation d050017f-3c3b-4d3e-99c2-06bb8a50a60f · outbound

This paper cites URL: https://huggingface.co/ datasets/data-is-better-together/10k_prompts_ranked, accessed: 2025-06-19.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter URL: https://huggingface.co/ datasets/data-is-better-together/10k_prompts_ranked, accessed: 2025-06-19

Reference 43

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source=pdf_text observed=2026-08-03T00:49:52.562625Z digest=sha256:7c7048ebc5ddacca770d638ded3c9c8357c61a1e5529dadde0a8037c2e0a72ea

Observation 3e0e0e0a-35fc-44da-b996-9c3225916eb8 · outbound

This paper cites Kundu, Prompt optimization dataset, 2025.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Kundu, Prompt optimization dataset, 2025

Reference 44

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source=pdf_text observed=2026-08-03T00:49:52.564541Z digest=sha256:61ed1209da7cc2e4ddba3f33b369b9a05254a145270fd5b803612ac44904fa57

Observation 355135fa-51bd-4cc8-8a2c-c1e194a05e7e · outbound

This paper cites Accessed: 2025-06-19.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Accessed: 2025-06-19

Reference 45

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source=pdf_text observed=2026-08-03T00:49:52.566517Z digest=sha256:8be4a2b60276bc94de4ea3080c1d481bd65e65ba4f20ac5f39305c32342fbae5

Observation 58351d14-ef28-41ec-8162-d52af948c834 · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 46

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no resolver link, observed 2026-08-03T00:49:52.568811Z

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source=pdf_text observed=2026-08-03T00:49:52.568811Z digest=sha256:6a369cb29a16ee984b35ecd2ee6c82bd113395f1ab2e68ba43bd20c4df33add9

Observation 830ad9eb-ae4f-4d30-8e7f-10610aa4acf6 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Understanding R1-Zero-Like Training: A Critical Perspective

Reference 47

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source=pdf_text observed=2026-08-03T00:49:52.572798Z digest=sha256:6e709ee90973df38165b06307a237f8c3ef467be4aebc84bb249b70372825bda

Observation b51b936f-9d6e-4da0-acde-e1f9cb347d34 · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 51

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source=pdf_text observed=2026-08-03T00:49:52.570862Z digest=sha256:81608cdee56ed8fe36b8e594731393ac2a73e0d95dac72df6e16ffc5367e7396

Observation 59515f74-079d-4017-94e7-cca4fbf425c0 · outbound

This paper cites explanation.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter explanation

Reference 53

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source=pdf_text observed=2026-08-03T00:49:52.575342Z digest=sha256:500d73e84b310b4e76f096ea270437a098cc5bf0383fca2914766faff23f86f9

Observation c7a0e2d6-25aa-45cb-a7ab-8ef930d042bb · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 54

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source=pdf_text observed=2026-08-03T00:49:52.577442Z digest=sha256:4010ec8682ba53cbf0257b3ace0d7777bde633ab08d67adb565a341c9d490866

Observation a75553a1-9b57-4224-8e20-354d578d20bd · outbound

This paper cites an unresolved cited work.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-03T00:49:52.579599Z digest=sha256:37752551370e258f8b2bdba366d051e970b9e35e952ac24bceb8dc73e09a5eac

Observation ed7688ad-24e9-460a-a3d2-04475b0fe2b2 · outbound

This paper cites explanation.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter explanation

Reference 56

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source=pdf_text observed=2026-08-03T00:49:52.581552Z digest=sha256:70c8738a8fe857ccedbabc7e8236925bf9d4150af77c4cb0bf3e26ceda079f38

Observation 5e25b91d-f99a-48cc-8132-ebbbf0d2d31c · outbound

This paper cites Proximal Policy Optimization Algorithms.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Proximal Policy Optimization Algorithms

Reference 2017

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source=pdf_text observed=2026-08-03T00:49:52.477326Z digest=sha256:c15bf05d4419ec1f9f763144c9ad0b40b3e496da1292cb19cdad13131b848c04

Observation 992c01d1-dab5-4750-adfd-85afdbdd0435 · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter Large Language Models are Zero-Shot Reasoners

Reference 2023

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source=pdf_text observed=2026-08-03T00:49:52.499165Z digest=sha256:72c4284924b6f67c0ca5f2a3cf248dfcb3bda467bb582a8c9d5f1686963a8c14

Observation ed441745-1b5e-496b-bcca-64b51fc976b0 · outbound

This paper cites RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 2024

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source=pdf_text observed=2026-08-03T00:49:52.535408Z digest=sha256:94889633f10eb4b1fcd6f8cebb906f59d2ad0caaf0e0ebe2d90a43daebb479ad

Observation 526fd29a-b086-417f-9cb9-baa65de1a544 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2025

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source=pdf_text observed=2026-08-03T00:49:52.490541Z digest=sha256:5d5b9f03e4f206dae2dd5df8d7d3d8bed984352ffb1e9c8e5e8aa0f857e2c500

Pith citing papers

No inbound Pith citation observations are available.