Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.284265Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.289189Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.294164Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.298578Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.302831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: verified fuzzy; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.320067Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.324172Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.327884Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: verified fuzzy; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.339406Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.346911Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.350926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.355334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.359365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.363233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.367597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.375136Z

Source-reported events for the cited work

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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

Resolution: verified exact; 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.383167Z

Source-reported events for the cited work

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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

Resolution: 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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: 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 2026-08-14T06:32:32.682623+00:00.

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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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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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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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

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

Source-reported events for the cited work

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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-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:20:01.858626Z

Source-reported events for the cited work

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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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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

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

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.426657Z

Source-reported events for the cited work

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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

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

Source-reported events for the cited work

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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

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

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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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.446134Z

Source-reported events for the cited work

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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

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

Source-reported events for the cited work

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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

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

Source-reported events for the cited work

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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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.