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Paper Citation Record · LEDGER

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework

As of 20 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 3 inbound Pith citation observations for arXiv:2506.05695.

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

pith.paper-citation-record.v1
2506.05695 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:20:01.458159Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T05:14:12.795412Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:59:42.571077Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact1
  • verified fuzzy13
  • unresolved30
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cfe8611f-0d0e-4692-8726-195db827e506 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Distilling the Knowledge in a Neural Network

Reference 1

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source=pdf_text observed=2026-08-07T10:20:01.279316Z digest=sha256:5dd862c5931f1ed9972b50281d10046130d33744ab6502a7b814dd862e168964

Observation 99bdbf87-0aff-4dcd-b962-80c1bea9f7ac · outbound

This paper cites f-Divergence Minimization for Sequence-Level Knowledge Distillation.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework f-Divergence Minimization for Sequence-Level Knowledge Distillation

Reference 2

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source=pdf_text observed=2026-08-07T10:20:01.284265Z digest=sha256:de753cec8bc75c4f0a7cc74148976ae960e0436b26407cdee6c374f903b12fb1

Observation 087c71f0-6667-4297-8cc2-07fcdc99ece5 · outbound

This paper cites DistiLLM: Towards Streamlined Distillation for Large Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 3

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source=pdf_text observed=2026-08-07T10:20:01.289189Z digest=sha256:b259618f2e83d020f89361ec818f45c89992d4299dc8bef97e055df81422fad5

Observation ec85ab1b-c6d9-4403-bfdb-825bf0e744d2 · outbound

This paper cites On-policy distillation of language models: Learning from self-generated mistakes.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework On-policy distillation of language models: Learning from self-generated mistakes

Reference 4

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source=pdf_text observed=2026-08-07T10:20:01.294164Z digest=sha256:bb8e6cbc47fef1e4eb9b39067eb2b78775f2c696186bb2c8fc2687e92cf472dd

Observation d449558b-00b9-4508-a59c-fed70d04db23 · outbound

This paper cites Training language models to follow instructions with human feedback.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Training language models to follow instructions with human feedback

Reference 5

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source=pdf_text observed=2026-08-07T10:20:01.298578Z digest=sha256:aac7a3bdf1a139e3c7886ea8404234e5f8c30d384d19f148d7471eb39327a72f

Observation ff6082c2-8adb-4f8c-b719-98273d3ab173 · outbound

This paper cites The Costly Dilemma: Generalization, Evaluation and Cost-Optimal Deployment of Large Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework The Costly Dilemma: Generalization, Evaluation and Cost-Optimal Deployment of Large Language Models

Reference 6

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source=pdf_text observed=2026-08-07T10:20:01.302831Z digest=sha256:9f9dad6a0ee733876ca6695006fd78cf3d34614a55402539b67de5f4c3a2f293

Observation 76182876-9682-4f62-a43f-5ab776362382 · outbound

This paper cites Pre-trained language models for text generation: A survey.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Pre-trained language models for text generation: A survey

Reference 7

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raw_fallback, observed 2026-08-07T10:20:02.016507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.308114Z digest=sha256:a0517b1981aad24f675d579c83156539f327d1f39f11d1e9e29f850f6003a3e2

Observation 554cb334-70ec-4744-890d-4030551af22a · outbound

This paper cites Confucius: Iterative tool learning from introspection feedback by easy-to-difficult curriculum.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Confucius: Iterative tool learning from introspection feedback by easy-to-difficult curriculum

Reference 8

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raw_fallback, observed 2026-08-07T10:20:02.003839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.312564Z digest=sha256:7867ec88234858396d7da21a884d953d6384eb348cda6e83e0885d5d9cb1ad70

Observation b2aae059-d1b1-4590-82c9-8ef2f82a2cce · outbound

This paper cites Llama 3.2: Revolutionizing edge ai and vision with open, customizable models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Llama 3.2: Revolutionizing edge ai and vision with open, customizable models

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T10:20:01.990963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.316246Z digest=sha256:667d071d73104d45cfbcaee7551671db45e42fe4e77244f61036da906edd23ca

Observation 7145e623-0141-4c7a-8ec7-247a8d2b7057 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Gemma 2: Improving Open Language Models at a Practical Size

Reference 10

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source=pdf_text observed=2026-08-07T10:20:01.320067Z digest=sha256:e05e57de9ebb495d4ea6f19ed311826e34666b153e6a9e6357e2ea7e7107001b

Observation 909d9c47-2dd2-4c7c-9acf-444bcda42be9 · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025

Reference 11

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source=pdf_text observed=2026-08-07T10:20:01.324172Z digest=sha256:9b07c061fd257f7e22508c718f36a0cf7eb7c815e078acc2a7c12c071417e2e6

Observation 9ad5a208-92f2-4fbd-b237-142226846866 · outbound

This paper cites A Survey on Knowledge Distillation of Large Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework A Survey on Knowledge Distillation of Large Language Models

Reference 12

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source=pdf_text observed=2026-08-07T10:20:01.327884Z digest=sha256:5bc357aa1b857e99491531042bbc324ef4c827e44fa87bff168cc8d07369e7c9

Observation 8486cf3f-9043-4f36-835c-e3c1c610d311 · outbound

This paper cites Survey on knowledge distillation for large language models: methods, evaluation, and application.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Survey on knowledge distillation for large language models: methods, evaluation, and application

Reference 13

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raw_fallback, observed 2026-08-07T10:20:01.967781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.331845Z digest=sha256:2c32ce8900f47b0db944437a397737fb6c9597eaff3716c584b51685760179f8

Observation 3fef852f-34a6-4a9a-a561-875ad5606993 · outbound

This paper cites Sequence-level knowledge distillation.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Sequence-level knowledge distillation

Reference 14

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raw_fallback, observed 2026-08-07T10:20:01.952778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.335570Z digest=sha256:3f68ca4f5687c8f74268a3fa9bbc2c2d15cb918f0d96c1e27fa9baf4f0770562

Observation e91cefaa-b4c5-4dd6-95d6-cf4dca159b0f · outbound

This paper cites GPT-4o System Card.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework GPT-4o System Card

Reference 15

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source=pdf_text observed=2026-08-07T10:20:01.339406Z digest=sha256:5b4035495336f2bb1aeea30021fbd10a3df16fc9700eccfbf3a81ee88d99c223

Observation dfdb7dd3-5fdc-4aa1-ac08-63e274d34596 · outbound

This paper cites Claude 3.5 Sonnet.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Claude 3.5 Sonnet

Reference 16

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raw_fallback, observed 2026-08-07T10:20:01.940346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.343014Z digest=sha256:b70df259522d9f3a877ed024121d31ded916123c377e3b5ffa99bc1c4926ce7d

Observation bf021401-785a-4cd0-9c92-7afa6b871046 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 17

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source=pdf_text observed=2026-08-07T10:20:01.346911Z digest=sha256:0af6b5a14f0bdfd6c974dc0e8956b2adcd8fdce770dd6b5e24c394b14f5fc313

Observation 501a2670-797f-4e85-91e8-5a146080751f · outbound

This paper cites Learning to Retrieve In-Context Examples for Large Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Learning to Retrieve In-Context Examples for Large Language Models

Reference 18

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source=pdf_text observed=2026-08-07T10:20:01.350926Z digest=sha256:36759c65f5108e196907fd2f8b1c0799a2056fd9f890979075b395aee23acd85

Observation a8f379ae-1790-4372-96fd-6daaf0c6884b · outbound

This paper cites Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Reference 19

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source=pdf_text observed=2026-08-07T10:20:01.355334Z digest=sha256:455753f3f7a4b03cecd4285a179cbce0c40113acbeed0a743a1d4a8f31e3b3f2

Observation 4e6b7ab7-546e-4c46-9f10-18aa6b51ec3e · outbound

This paper cites Instruction Tuning with GPT-4.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Instruction Tuning with GPT-4

Reference 20

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source=pdf_text observed=2026-08-07T10:20:01.359365Z digest=sha256:fddb307ca5821a9e2f562ac81aca7efcef31374b67a137d4cd7fb8bdbdda84b1

Observation 22dd1424-f88b-40b2-8377-9f339a836db4 · outbound

This paper cites DeepSeek-V3 Technical Report.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework DeepSeek-V3 Technical Report

Reference 21

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source=pdf_text observed=2026-08-07T10:20:01.363233Z digest=sha256:9101f2cb77db49818cc1aa2f9ac0d27dfcc07dafa8ec6d4a9e3acc34a24c25ff

Observation 2531d07b-e529-44a1-8225-c0ac21d390d5 · outbound

This paper cites Qwen2.5 Technical Report.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Qwen2.5 Technical Report

Reference 22

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source=pdf_text observed=2026-08-07T10:20:01.367597Z digest=sha256:056f3cc98eb56df4f08002d83fa666162ce160e5aea24999a15c294c21e7df62

Observation 4c20a7dc-d7bd-45c2-b779-8600b3dadb3c · outbound

This paper cites The ai index 2025 annual report.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework The ai index 2025 annual report

Reference 23

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raw_fallback, observed 2026-08-07T10:20:01.927262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.371223Z digest=sha256:6f25de8c9f5ee1b2b14eee0f6685ec592acc488a5e57b4646724dce1bc400a45

Observation 13e65741-fe89-4980-a479-afc08823d841 · outbound

This paper cites MiniLLM: On-Policy Distillation of Large Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework MiniLLM: On-Policy Distillation of Large Language Models

Reference 24

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source=pdf_text observed=2026-08-07T10:20:01.375136Z digest=sha256:b63975700676633ee799291d7e6aaedd9549cc17f518d6b1769043ef41477a69

Observation 70bf6e29-f7cc-4636-ac7f-62e44b09a863 · outbound

This paper cites Autoregressive Knowledge Distillation through Imitation Learning.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Autoregressive Knowledge Distillation through Imitation Learning

Reference 25

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local_arxiv, observed 2026-08-07T10:20:01.605055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.379230Z digest=sha256:01c819ec9bbc1ac4975249f4057ed6ffed5c765c46c898ec31204874cf7252ef

Observation a41afb16-ac05-4c5b-85d2-c0662c65a0e7 · outbound

This paper cites Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling

Reference 26

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source=pdf_text observed=2026-08-07T10:20:01.383167Z digest=sha256:efdacad0ebfc88ee5a60f820d93927c9adeccd08a181d6967d7c2577b5e05496

Observation eea00772-dfae-42b5-b0b4-7ecc4f2918d8 · outbound

This paper cites A survey on curriculum learning.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework A survey on curriculum learning

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T10:20:01.914929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.387674Z digest=sha256:bbe8e1f55b2fdb6c44268c5e5dba23e64eab05db9e13859daf52b6771b4cc839

Observation ee208c69-13c5-4d72-8f42-c13b2aa9dc20 · outbound

This paper cites Science and practice of strength training.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Science and practice of strength training

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T10:20:01.901922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.391904Z digest=sha256:93296fa98da7254bdcf858f2e757e30eeb61261e2cf16efd47872d7ab0256c9e

Observation 3787f6e1-e927-498d-817e-42da0b49e7eb · outbound

This paper cites Dual-Space Knowledge Distillation for Large Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Dual-Space Knowledge Distillation for Large Language Models

Reference 29

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source=pdf_text observed=2026-08-07T10:20:01.395817Z digest=sha256:36c1ba644ea389ae1ea9f051a6dc38ea1c3e718ee4e20f696eee25c899b2c1cb

Observation f38d6d3c-12ca-44f1-9aa6-febd0d802f9c · outbound

This paper cites Revisiting Catastrophic Forgetting in Large Language Model Tuning.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Revisiting Catastrophic Forgetting in Large Language Model Tuning

Reference 30

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source=pdf_text observed=2026-08-07T10:20:01.399991Z digest=sha256:b923aa373ff651f16d4a7285250706f77f8fbe1e701f386c6e8e9f9711e934d0

Observation d62ba192-4517-4bbb-b323-60ac91ea3a8f · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Rouge: A package for automatic evaluation of summaries

Reference 31

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source=pdf_text observed=2026-08-07T10:20:01.403847Z digest=sha256:1f2fc86c22a4a8f23798302cf9a177632db84447afc19d73d5c737b566d51bf7

Observation 48038b3f-e65f-4447-b8f2-40563458cd2d · outbound

This paper cites Reciprocal rank fusion outperforms condorcet and individual rank learning methods.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Reciprocal rank fusion outperforms condorcet and individual rank learning methods

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T10:20:01.880064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.407506Z digest=sha256:3128af2dc99bf998c0b49c977ab6853e166ebdcb24188c622bd7dfce93afd533

Observation 941cc7dd-cb52-4f21-9f7d-0a80f01bb12e · outbound

This paper cites Curriculum learning.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Curriculum learning

Reference 33

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source=pdf_text observed=2026-08-07T10:20:01.411150Z digest=sha256:ed51a822948094d261778ea55196acef1a3784a1231b22a90b3f5bbab3422fd0

Observation 346ecbfb-d1e5-45da-9445-991f73847409 · outbound

This paper cites A comparison of most-to-least and least-to-most prompting on the acquisition of solitary play skills.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework A comparison of most-to-least and least-to-most prompting on the acquisition of solitary play skills

Reference 34

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raw_fallback, observed 2026-08-07T10:20:01.858626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.414884Z digest=sha256:9a8c6d7a9dbe7e22dc212d0cf805cfdf75788f89fbfc6a1568707c88be432b09

Observation ec28595b-bcb1-4080-9b71-d5b9e3757c26 · outbound

This paper cites Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023

Reference 35

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no resolver link, observed 2026-08-07T10:20:01.418825Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:20:01.418825Z digest=sha256:5690006a1a4bfa87bd140f42f7310cb42753612ae3820f6cb02d70d74f040370

Observation 98f27c66-8594-4e69-b199-c6505d9e1f58 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 36

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unresolved
no resolver link, observed 2026-08-07T10:20:01.422462Z

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source=pdf_text observed=2026-08-07T10:20:01.422462Z digest=sha256:bf3fbe97e08472ad4e4dfa887dedb6923d0e7859d4d08f698fee33c7d4e448d9

Observation 45a81177-c92b-4e73-8837-03a68102db57 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 37

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source=pdf_text observed=2026-08-07T10:20:01.426657Z digest=sha256:341cf90f5a3744a53fe375b6c480fac2a404b91c61ce78fdf090d2765a72d1d1

Observation 47cfcfbe-e28c-45e5-a7f0-6c88f257d8a4 · outbound

This paper cites Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Reference 38

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no resolver link, observed 2026-08-07T10:20:01.430323Z

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source=pdf_text observed=2026-08-07T10:20:01.430323Z digest=sha256:3b793dfe87c8044671344b92901dc8de2c8db44abb898472d950813686273a6f

Observation 893df899-ab89-4c4f-9307-5cdd9138c26e · outbound

This paper cites Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 39

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no resolver link, observed 2026-08-07T10:20:01.434515Z

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source=pdf_text observed=2026-08-07T10:20:01.434515Z digest=sha256:fde8ce5d53aa584a679ee835f7bc0454c3d670c849e2c2ec00c15ab5a9c8fcc4

Observation df4d3779-68c0-4e42-b580-b3b4a531eede · outbound

This paper cites Learning from multiple experts: Self-paced knowledge distillation for long-tailed classification.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Learning from multiple experts: Self-paced knowledge distillation for long-tailed classification

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:01.829077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.438405Z digest=sha256:9cd39d2182d10d85d2ad23ee5eac21955e6fe38527b33f3341795f1a645249c0

Observation eab608f7-cb61-43c2-9c11-ca6d61773501 · outbound

This paper cites Curriculum tem- perature for knowledge distillation.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Curriculum tem- perature for knowledge distillation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:01.814690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.442260Z digest=sha256:2d19d85036cf96328d22d3959f05d8949b4d37c0e1ef7b363293c935e191f51f

Observation 144e9747-c2a9-48fd-ba9d-77015d787b9e · outbound

This paper cites DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs

Reference 42

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source=pdf_text observed=2026-08-07T10:20:01.446134Z digest=sha256:610b2842360952596c0c42b1f171e678236b1a1e0f8e908b7caa731dce6ea1d2

Observation 26164519-8375-4b24-8118-c2914c9f93b9 · outbound

This paper cites Language models are unsupervised multitask learners.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Language models are unsupervised multitask learners

Reference 43

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no resolver link, observed 2026-08-07T10:20:01.450127Z

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source=pdf_text observed=2026-08-07T10:20:01.450127Z digest=sha256:6de352619a645fe96ed97ee5bb0594d672dd087b4ff638933148aacaf0be8233

Observation cb378345-090f-45fb-952d-19319c059348 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework OPT: Open Pre-trained Transformer Language Models

Reference 44

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no resolver link, observed 2026-08-07T10:20:01.454112Z

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source=pdf_text observed=2026-08-07T10:20:01.454112Z digest=sha256:bb95ce46e681365088849a62cb874f3fd836fc1e8d44df7c5be9af48f398238e

Observation d907fa2b-8ea7-4e2c-ba86-16dad332578e · outbound

This paper cites Qwen3: The latest large language model series from alibaba cloud, 2025.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Qwen3: The latest large language model series from alibaba cloud, 2025

Reference 45

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T10:20:01.793316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T10:20:01.458159Z digest=sha256:601542b5621fe969979c07e816303c4c443179dcd7efd4569f3b098d39303998

Pith citing papers

Observation eda96db4-1ee8-4b8f-9031-796e77a95c74 · inbound

Curriculum Learning-Guided Progressive Distillation in Large Language Models cites this paper.

Curriculum Learning-Guided Progressive Distillation in Large Language Models Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:57:05.839700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-13T01:53:21.920498Z digest=sha256:d1448c8ada29a03c873349fc85d47f715b157e2fee124127e4092104546cfbdc

Observation a08082e3-8364-4216-b925-ec25bacfd720 · inbound

On the Position Bias of On-Policy Distillation cites this paper.

On the Position Bias of On-Policy Distillation Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:59:42.572759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T10:45:16.028763Z digest=sha256:cb904cdae1b34e1603ba461521d1bc2b2e8063ce7da2509b657f1a2b68579cfb

Observation 6226bddf-3b5e-4b17-88d2-2e8561ce7600 · inbound

On the Position Bias of On-Policy Distillation cites this paper.

On the Position Bias of On-Policy Distillation Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-06-29T18:13:49.263364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-29T05:14:12.795412Z digest=sha256:41da96c1ce8bb3dd906778fffefba6555fa1610cabe6dd61f3086f71d1f9a54a