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Paper Citation Record · LEDGER

DistiLLM: Towards Streamlined Distillation for Large Language Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 45 inbound Pith citation observations for arXiv:2402.03898.

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

pith.paper-citation-record.v1
2402.03898 v2

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 45 of 45 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:13:22.755979Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

4
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ca37dec1-f373-4fd3-a31f-644000543747 · inbound

Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models cites this paper.

Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 19

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no resolver link, observed 2026-08-12T12:45:19.955519Z

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Observation 381fdb64-d263-45d2-a983-52bb9588d22d · inbound

Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models cites this paper.

Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 25

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no resolver link, observed 2026-08-11T12:15:18.565667Z

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source=arxiv_source observed=2026-08-11T12:15:18.565667Z digest=sha256:5bf3e9c9b5c78b38baebbd06b9405be268bd09aa9a63808fbe325658bb99433f

Observation b4832e30-4a5f-43b5-885c-03b680f0ca8a · inbound

Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation cites this paper.

Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 19

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no resolver link, observed 2026-08-11T15:09:39.100484Z

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source=arxiv_source observed=2026-08-11T15:09:39.100484Z digest=sha256:addf614af7f27f8ae5fef56f0bdc75f6c8c94d679be74fb52ef4169eda3df3d2

Observation 48187e72-3c62-4e3c-9f0f-395e3997ecc9 · inbound

Self-Evolution Knowledge Distillation for LLM-based Machine Translation cites this paper.

Self-Evolution Knowledge Distillation for LLM-based Machine Translation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 20

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source=arxiv_source observed=2026-08-11T11:59:54.856784Z digest=sha256:cdbe37383bfb237d3ccc4552785245c95f2fcb7db34c3fbefe13ac0787f3e537

Observation 5ffc08f1-601f-4e35-9474-87a827ab0d02 · inbound

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion cites this paper.

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 21

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source=arxiv_source observed=2026-08-10T22:08:34.862859Z digest=sha256:a6ad664b21791b5f2d2e1092feb37e196ea3d80bb79a5f1f3e088a133653fed4

Observation a279f826-24db-4d48-aab9-79be8b390922 · inbound

DNA 1.0 Technical Report cites this paper.

DNA 1.0 Technical Report DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 11

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no resolver link, observed 2026-08-10T19:04:34.962552Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:04:34.962552Z digest=sha256:e9c0d503f9c2de59b7f3080a59e3592ca80ca73cee781306e8f850cf70324808

Observation 994244e9-e0b4-4f92-95d3-d3765efae91b · inbound

On Accelerating Edge AI: Optimizing Resource-Constrained Environments cites this paper.

On Accelerating Edge AI: Optimizing Resource-Constrained Environments DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 93

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no resolver link, observed 2026-08-10T14:46:38.501603Z

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source=arxiv_source observed=2026-08-10T14:46:38.501603Z digest=sha256:ae90643a268b964851349489ac3170e4fe626a97ee780a10fd96e21faa15c209

Observation bab0a534-e073-49c7-ad5c-4fdaa397ab83 · inbound

EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models cites this paper.

EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 19

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no resolver link, observed 2026-08-08T14:48:53.789335Z

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source=pdf_text observed=2026-08-08T14:48:53.789335Z digest=sha256:8a8b9622ae373d708e470d444ee52de57c8ec42a099ed109d9880504a2162e9a

Observation 20fda6c1-d7c0-4f50-ab19-4587b76ef855 · inbound

Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion cites this paper.

Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 3

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source=pdf_text observed=2026-08-16T11:13:22.755979Z digest=sha256:6317f2b1d038e6482d4ed73da628cde6d06ad735807d2cd9f5666a0e00de3c5a

Observation 97676631-4632-4726-90e7-37cafba6c385 · inbound

Optimizing LLMs for Resource-Constrained Environments: A Survey of Model Compression Techniques cites this paper.

Optimizing LLMs for Resource-Constrained Environments: A Survey of Model Compression Techniques DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 22

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source=pdf_text observed=2026-08-16T01:00:02.023103Z digest=sha256:a5ef8f9041769815230d2370b610011232f5add6612ef7a8319796494be18d8f

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

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

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

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

Observation 8e479b64-4769-4745-8936-23e0b4357318 · inbound

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs cites this paper.

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 7

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source=pdf_text observed=2026-08-07T05:04:03.157167Z digest=sha256:4301ab1ae0a6bc910eddc7accd31edb6e5a529ae97987a16fadd9d962e4c2965

Observation 5cdf9751-0f79-4855-8afd-44e3ebced1bd · inbound

CKD-EHR:Clinical Knowledge Distillation for Electronic Health Records cites this paper.

CKD-EHR:Clinical Knowledge Distillation for Electronic Health Records DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 11

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source=pdf_text observed=2026-08-15T19:47:26.188921Z digest=sha256:ef697ebc0df69e5982c17ce7715c05af678179de83d0ba0094b434553ce58ca1

Observation b777241c-171e-42da-9dbd-2d7149f8f076 · inbound

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models cites this paper.

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 46

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source=pdf_text observed=2026-08-06T23:57:23.472738Z digest=sha256:0626faf8af315e300ce9c8e6f093f019b7be5f2782fce397104ee870956a645a

Observation afb47b9a-9024-441a-b97a-73df6cff3a7a · inbound

DipSVD: Dual-importance Protected SVD for Efficient LLM Compression cites this paper.

DipSVD: Dual-importance Protected SVD for Efficient LLM Compression DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:58:09.354241Z digest=sha256:9dc653b05781b13ad62e6466fad31b1a1bc0a05c7ed20938981bc135e7195abb

Observation bf1372cb-2c2d-4815-b264-30df58d36e6d · inbound

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation cites this paper.

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 25

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source=arxiv_source observed=2026-08-06T22:45:01.602702Z digest=sha256:33994fde460b53daa19a08cf87ae1c5f3268594bb61132fb584337e68852c511

Observation bd44b6ad-7232-4790-8296-22323b63afb4 · inbound

GPO: Learning from Critical Steps to Improve LLM Reasoning cites this paper.

GPO: Learning from Critical Steps to Improve LLM Reasoning DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 22

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source=pdf_text observed=2026-08-15T15:55:56.138663Z digest=sha256:3c1bad87797c1c53c452233ac9acaa69986e15672272567bdb7735cc81b3729a

Observation 8a4f3613-9185-441e-8e0b-a14583187ad8 · inbound

SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting cites this paper.

SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 13

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source=pdf_text observed=2026-07-12T22:24:51.874340Z digest=sha256:84d5a217f6b47266d05b93506e1b090cc3045a9d22c1a2b9b448b740ac7ecb76

Observation 25b3d109-edcc-4ec3-9525-689323846b11 · inbound

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models cites this paper.

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 19

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arxiv_id, observed 2026-05-10T11:25:18.532570Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 5460ef4e-539c-48c5-968d-a219b717c64f · inbound

Hybrid Policy Distillation for LLMs cites this paper.

Hybrid Policy Distillation for LLMs DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 47

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arxiv_id, observed 2026-05-10T00:54:49.028037Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-10T00:41:21.984760Z digest=sha256:cc56acd0a757402a7e1433cb77ded6131d8c578a7a8ed404c07cd2c548cfa704

Observation d2ace319-c448-4eef-b9ee-fc47d2760ef3 · inbound

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation cites this paper.

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 77

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arxiv_id, observed 2026-05-11T16:51:05.560395Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-09T14:55:26.285575Z digest=sha256:ddefba0013b35eee490ec4d4dd99dccaa7b1fefe251c6b21f0a9e483bac14b33

Observation 22128e69-fbca-4a4d-9f98-4c8ee4151840 · inbound

Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing cites this paper.

Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 11

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arxiv_id, observed 2026-05-11T18:41:11.258763Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T14:20:37.141500Z digest=sha256:ec622b330494bc98985cabc047210c3a80002fa1f2c1e2956f33c1662ddbbba4

Observation f8300bd2-957c-4c41-8eb7-dc6f92b05adb · inbound

The Extrapolation Cliff in On-Policy Distillation of Near-Deterministic Structured Outputs cites this paper.

The Extrapolation Cliff in On-Policy Distillation of Near-Deterministic Structured Outputs DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 21

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arxiv_id, observed 2026-05-12T07:06:36.519788Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-12T03:43:16.720945Z digest=sha256:657c30bdbae178d5eb5850eab17dd3055a30a820962958fc1d637301b3c3f19d

Observation 4481a242-61fc-467a-8bfa-caba6dc58ae6 · inbound

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

Curriculum Learning-Guided Progressive Distillation in Large Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 26

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arxiv_id, observed 2026-05-13T01:57:05.823128Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation bfffa97a-b11a-4121-b33d-29bbc0db482e · inbound

Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation cites this paper.

Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 9

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arxiv_id, observed 2026-05-14T21:28:00.258090Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-14T21:23:15.511083Z digest=sha256:632f144a5c347258f1e03d1b2ce37ab4dc75239f9c50b80e5a003ce138fbbf3e

Observation 9eaf2427-19ab-454d-af7e-5b8207d49198 · inbound

MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation cites this paper.

MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 63

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arxiv_id, observed 2026-05-20T12:53:28.543541Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-20T12:53:20.761872Z digest=sha256:5b637a58bb52af7564570349fb7c1a158893c28e53c37573920dcc9b61d14e42

Observation 04227a4c-c5b2-412b-8eed-1fc2e91a6002 · inbound

When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning cites this paper.

When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 20

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arxiv_id, observed 2026-05-22T09:26:20.581767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7c5fbd27-8657-4e24-8198-00f7d6280272 · inbound

Visual-Advantage On-Policy Distillation for Vision-Language Models cites this paper.

Visual-Advantage On-Policy Distillation for Vision-Language Models DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 4

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verified exact
arxiv_id, observed 2026-05-22T07:24:42.929750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T07:24:22.355378Z digest=sha256:eeec2e7daf30d745dcd7a086f7281aafb364b6ad6ef966e5b6371367fc9be9ca

Observation 42024a70-d33c-4a87-886a-3da384f2c19b · inbound

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation cites this paper.

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 12

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arxiv_id, observed 2026-06-29T08:53:15.857113Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T08:50:41.083288Z digest=sha256:a4aa4b83bb7883c94cce8c8189e3ba3ea6af2723b1ac05c480f9a608dd0eb141

Observation 38722acb-1395-4ab4-81df-c831c34b1361 · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 117

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arxiv_id, observed 2026-06-28T23:32:46.502050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-28T23:29:02.457697Z digest=sha256:ff48ca944848e4659c2479286cd8bcdf40a25f0ab6674ea7575dbbb0540f70c3

Observation 5c01b4d8-3945-4919-a27e-65c3b065498d · inbound

PriFT: Prior-Support Guided Supervised Fine-Tuning cites this paper.

PriFT: Prior-Support Guided Supervised Fine-Tuning DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 12

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arxiv_id, observed 2026-07-03T00:57:29.941581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T16:58:09.015766Z digest=sha256:6ad41774180a0646a8428b04744482fbf78d5a354e1f03360680179b7e513b0b

Observation 6e5b53cd-d166-447d-8a7e-2d7a863224ec · inbound

RLCSD: Reinforcement Learning with Contrastive On-Policy Self-Distillation cites this paper.

RLCSD: Reinforcement Learning with Contrastive On-Policy Self-Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 15

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arxiv_id, observed 2026-07-03T09:07:48.375782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T10:28:18.490452Z digest=sha256:45f8db2d3d8a7f31e3c1d71806213e6444ea545559fc71e4c080085e10f5de99

Observation 390eb2f4-b160-4077-9735-dbc06f3613c8 · inbound

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients cites this paper.

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 21

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arxiv_id, observed 2026-07-03T20:48:56.150486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T01:08:52.981296Z digest=sha256:3a9b1435742e7676cb68dfdd613407b88f3131251ef9cb3c54a4c4908aa3fd1b

Observation bede0ac8-83e3-4d0f-92cd-3f6400106332 · inbound

PHF: Privileged Hidden Flow for On-Policy Self-Distillation cites this paper.

PHF: Privileged Hidden Flow for On-Policy Self-Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 3

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arxiv_id, observed 2026-06-30T07:34:21.814445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-30T07:26:32.902086Z digest=sha256:85ad9fd286a33a7f777a48642e6b7ef32ae9ab0aebfc45d1cb9b1649a60d40ab

Observation f3675b32-7ab2-4005-a5f1-ee3b584baea0 · inbound

Weak-to-Strong Generalization via Direct On-Policy Distillation cites this paper.

Weak-to-Strong Generalization via Direct On-Policy Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 35

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verified exact
local_arxiv, observed 2026-07-07T12:33:45.112342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-07T12:31:42.224094Z digest=sha256:83a747dc4334a1e1868526f3d178719448c51f80ea56563f7e298ee156929058

Observation e193e4c4-d4be-4125-9b9c-a5b283fa6f3b · inbound

Weak-to-Strong Generalization via Direct On-Policy Distillation cites this paper.

Weak-to-Strong Generalization via Direct On-Policy Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 35

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unresolved
no resolver link, observed 2026-07-11T07:01:56.628017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T07:01:56.628017Z digest=sha256:9f612b28cc061aa05c9f2363f89915c0a55cd14ef6885ba8cf868097fafe6ee3

Observation 6336b4f7-cc18-4380-beb2-d95329b794b9 · inbound

On-Policy Delta Distillation cites this paper.

On-Policy Delta Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 44

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unresolved
no resolver link, observed 2026-08-02T00:00:10.117823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:00:10.117823Z digest=sha256:443c0591c557ec9117e6a42fcf28d4eb2802487d6962d1c2be9d345fb4720399

Observation 1e7e9c5b-8ed8-4641-b1dc-3ca27c65684c · inbound

Med-OPD: Improving Medical Vision-Language Models via Evidence-Aware On-Policy Distillation cites this paper.

Med-OPD: Improving Medical Vision-Language Models via Evidence-Aware On-Policy Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 12

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unresolved
no resolver link, observed 2026-08-02T06:36:34.519466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:36:34.519466Z digest=sha256:dd7cebdaf3a02299c05bfed1df9427b7c25eb0847bbe2b7d05bb325ca5ecf319

Observation 1488b820-6824-4687-954a-28e0b376173d · inbound

Cross-Tokenizer On-Policy Distillation via Byte-Prefix Marginalization cites this paper.

Cross-Tokenizer On-Policy Distillation via Byte-Prefix Marginalization DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 40

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unresolved
no resolver link, observed 2026-08-01T05:09:56.913028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:09:56.913028Z digest=sha256:8ee73548a9d8cb9d69693cce90bf5c82a1d752f3b54812177b74ccebc3fbd84d

Observation 8ad81f8e-c470-4db2-ab72-2650a284f41f · inbound

Weak-to-Strong On-Policy Distillation cites this paper.

Weak-to-Strong On-Policy Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-01T00:26:25.081268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T00:26:25.081268Z digest=sha256:cffde4529912b559ed92ee425408fdde454ee9628dcd22c305986d5051fdfcef

Observation c1b745d8-005e-434f-8ad3-6f3bbae76750 · inbound

Not All Tokens Deserve Equal Credit: Counterfactual Sensitivity Credit Reallocation for Long-CoT Reasoning cites this paper.

Not All Tokens Deserve Equal Credit: Counterfactual Sensitivity Credit Reallocation for Long-CoT Reasoning DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 8

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unresolved
no resolver link, observed 2026-07-31T23:39:11.831350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:39:11.831350Z digest=sha256:4260c945dd7de53fb1fe6abe2d1ca8120d8ee03a489708ad1d2431b3cfc2cf31

Observation d5ea3033-7bfd-4d19-8426-a838f50f57e6 · inbound

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation cites this paper.

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T11:42:23.628684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:42:23.628684Z digest=sha256:e966692774b1e24d33a9e223758175236faf6601bd466a0153a811e064053267

Observation f592d38c-cecd-4fe3-80e4-942c4e0b34d8 · inbound

MemOPD: On-Policy Distillation through Memory State Alignment for Long-Horizon Agents cites this paper.

MemOPD: On-Policy Distillation through Memory State Alignment for Long-Horizon Agents DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:03.084232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:27:03.084232Z digest=sha256:d5f6845e93110ed440acc48513eef558c1131ee9bcb67f26bb7c6b880de03a59

Observation 6bed0a0b-3442-47ad-9654-7cd59b7a9f2f · inbound

Reliability-Safety Trade-off in AI Distillation: A Renormalization-Group Approach cites this paper.

Reliability-Safety Trade-off in AI Distillation: A Renormalization-Group Approach DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T04:42:22.396440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:42:22.396440Z digest=sha256:07ce42c2865f23501ea35f3cb0ad35e6821def45062252e094ba4ed887b61634

Observation 9dc29fc1-97b6-4435-9476-34db50f38de4 · inbound

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast cites this paper.

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast DistiLLM: Towards Streamlined Distillation for Large Language Models

Reference 9

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unresolved
no resolver link, observed 2026-08-14T04:31:40.926096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:31:40.926096Z digest=sha256:12f90a2464d904005e93293344475be099f9dfa69fe756ff5f1d5435468c648c