Pith. sign in

Paper Citation Record · LEDGER

Efficient Knowledge Injection in LLMs via Self-Distillation

As of 11 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 7 inbound Pith citation observations for arXiv:2412.14964.

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

pith.paper-citation-record.v1
2412.14964 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:52:37.270748Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

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

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:04:31.647548Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:56:47.730179Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved37
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 03e56360-c8f8-4595-8e27-5336625d58f7 · outbound

This paper cites GPT-4 Technical Report.

Efficient Knowledge Injection in LLMs via Self-Distillation GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.086452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.086452Z digest=sha256:c513960de962bca62ac854aa7a009e371eea90d0713307964199ddcc3580d14f

Observation 47d91a7d-ffe6-4e50-8395-36040de64166 · outbound

This paper cites Adapting Language Models to Compress Contexts.

Efficient Knowledge Injection in LLMs via Self-Distillation Adapting Language Models to Compress Contexts

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.104311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.104311Z digest=sha256:b85ae96475eade30a6a87fedf38f01f4727807472965973b1b391cb0b6274e93

Observation 56089bf7-56f8-46e6-a1b0-93035819f9a5 · outbound

This paper cites The Llama 3 Herd of Models.

Efficient Knowledge Injection in LLMs via Self-Distillation The Llama 3 Herd of Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.112713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.112713Z digest=sha256:78d43e797c8a163f8fca88a1616acfb51f3077492572b99e168da07e7dfdb04e

Observation 7470d0fb-9905-4fb6-9e1e-93189fe3665b · outbound

This paper cites The False Promise of Imitating Proprietary LLMs.

Efficient Knowledge Injection in LLMs via Self-Distillation The False Promise of Imitating Proprietary LLMs

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.116782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.116782Z digest=sha256:5c43b9c8a304b281d9728f9db65f52d5e91d23303d552e565707be0d65b8c7af

Observation 7796b37f-3803-4045-92a5-8329e84c5a90 · outbound

This paper cites Don't Stop Pretraining: Adapt Language Models to Domains and Tasks.

Efficient Knowledge Injection in LLMs via Self-Distillation Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.125237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.125237Z digest=sha256:3278c833cece90e6844e70e02f674131e935d5dc16392da58673ab3e78e8c72b

Observation 9578ef48-9612-46c7-8956-972139b897bf · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Efficient Knowledge Injection in LLMs via Self-Distillation Distilling the Knowledge in a Neural Network

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.134081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.134081Z digest=sha256:fc9e3231eaff91fe19760d22aee10ba41070f96538b86a02c0813ec58420f862

Observation 6126f122-a95f-4b8c-982d-f151609a3ea6 · outbound

This paper cites RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models.

Efficient Knowledge Injection in LLMs via Self-Distillation RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.143760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.143760Z digest=sha256:9235c01b965d792c6c60d9a52e1bf56ca977a4c41062e1d67bba0738bf758c60

Observation 2d269c3c-e99d-432c-9a0b-87bbf3a0aaa8 · outbound

This paper cites Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering.

Efficient Knowledge Injection in LLMs via Self-Distillation Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.148846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.148846Z digest=sha256:7248850748aaaef77da6404f286ffe0fa97f36a54ed1956c3b5c2522070d5fc9

Observation 805153a0-8015-4b22-91e7-c5dee28c07b2 · outbound

This paper cites Generalization through Memorization: Nearest Neighbor Language Models.

Efficient Knowledge Injection in LLMs via Self-Distillation Generalization through Memorization: Nearest Neighbor Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.153376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.153376Z digest=sha256:547a0f13ebcda1657842d7c7147083370b46897f80c21a9684011f80ce8c4bd6

Observation 763a6aab-fa9c-41fb-ac48-d46c6e206bb6 · outbound

This paper cites RA-DIT: Retrieval-Augmented Dual Instruction Tuning.

Efficient Knowledge Injection in LLMs via Self-Distillation RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.162226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.162226Z digest=sha256:90e7ba78c963d50b4e6e8a29af27d93c02bbe581eaf866375d7280778b98f792

Observation e457e219-f634-44d5-a729-f0ae9a5cce2f · outbound

This paper cites Structure-aware Domain Knowledge Injection for Large Language Models.

Efficient Knowledge Injection in LLMs via Self-Distillation Structure-aware Domain Knowledge Injection for Large Language Models

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-11T11:52:37.522227Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.167306Z digest=sha256:df5f5aadb52a8b196475d76981c8ea44ea53bc802d0c2ada663da1bdb78c5328

Observation ef842316-cf51-4bb9-a7ce-5973f06ce800 · outbound

This paper cites ChatQA: Surpassing GPT-4 on Conversational QA and RAG.

Efficient Knowledge Injection in LLMs via Self-Distillation ChatQA: Surpassing GPT-4 on Conversational QA and RAG

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.171818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.171818Z digest=sha256:9d0637e647b8fbcb50d573f9de00773e4c7386400ab37efceb8c33c839084ac9

Observation d9b8178e-5f41-4a8a-ab2b-ab4c75d8a82d · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

Efficient Knowledge Injection in LLMs via Self-Distillation When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.176676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.176676Z digest=sha256:23f5eab0da261b5f69c7751d84506b34510a90ce6a00b01c14c4835943a7e4e9

Observation 03a92b77-3952-4e84-b964-e741a3d76cf3 · outbound

This paper cites Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning.

Efficient Knowledge Injection in LLMs via Self-Distillation Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.181478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.181478Z digest=sha256:5d0d485f9b6c477675770e00564f61e74d040836ea2514a5a9fc94168b12543a

Observation e55a76c8-fa4c-4235-b91f-3c9b16d18ec2 · outbound

This paper cites Orca 2: Teaching Small Language Models How to Reason.

Efficient Knowledge Injection in LLMs via Self-Distillation Orca 2: Teaching Small Language Models How to Reason

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.186069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.186069Z digest=sha256:fb090e508fdc62d3253423ec9b5297334f6aaa9b3808edb9abdf631e2268ff2a

Observation 26f47e3f-fd91-49cd-95c9-4cc7954909a3 · outbound

This paper cites XtremeDistil: Multi-stage Distillation for Massive Multilingual Models.

Efficient Knowledge Injection in LLMs via Self-Distillation XtremeDistil: Multi-stage Distillation for Massive Multilingual Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.191047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.191047Z digest=sha256:c5b8143268f9d0f95ca64896f55b3a1d03d623412f3b722347862cb693689241

Observation 7fe94a89-d997-4c74-b92f-321de45756cd · outbound

This paper cites Orca: Progressive Learning from Complex Explanation Traces of GPT-4.

Efficient Knowledge Injection in LLMs via Self-Distillation Orca: Progressive Learning from Complex Explanation Traces of GPT-4

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.195772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.195772Z digest=sha256:e42f5be461416f09d0fbcd5fc658460bdaa9448283e3d91d3d0282468cc6cf28

Observation a180c0bd-0333-46ef-aed6-f19a61b16814 · outbound

This paper cites Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation.

Efficient Knowledge Injection in LLMs via Self-Distillation Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.200189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.200189Z digest=sha256:69b2f30ff9e7e97ac158696357564c8766ee961be4a9db6c07ecc749118e8ef3

Observation 46ae1da7-bb1f-4efc-9158-6a63d3e710b9 · outbound

This paper cites Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs.

Efficient Knowledge Injection in LLMs via Self-Distillation Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.204758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.204758Z digest=sha256:50f43eb1953660f908705a6ae5ee10bcdf5b77f15cf649c60f38d63748c5a8db

Observation a7e5019a-b4ba-410f-b011-5f50298570a3 · outbound

This paper cites Instruction Tuning with GPT-4.

Efficient Knowledge Injection in LLMs via Self-Distillation Instruction Tuning with GPT-4

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.209209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.209209Z digest=sha256:a3406117981c16c134ba0cbd25f325846a000d9d0132292dc26c79f8877c4436

Observation 1154c72e-e39c-4a94-93eb-bcfe8809d26c · outbound

This paper cites In-Context Editing: Learning Knowledge from Self-Induced Distributions.

Efficient Knowledge Injection in LLMs via Self-Distillation In-Context Editing: Learning Knowledge from Self-Induced Distributions

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.213565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.213565Z digest=sha256:3f3d9a32a3c8cb5f167fd95586665bdec20393fc0c475a2ad32c2950187d5c0a

Observation 9f8816d2-bda9-4d46-8d19-94c6926739ec · outbound

This paper cites Multitask Prompted Training Enables Zero-Shot Task Generalization.

Efficient Knowledge Injection in LLMs via Self-Distillation Multitask Prompted Training Enables Zero-Shot Task Generalization

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.222089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.222089Z digest=sha256:bd8950232143f0c95a58db908a5afdec3c27f4cc722628465629c92bbaff8024

Observation a716a0cc-f600-487b-afc5-c2031fd2c167 · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

Efficient Knowledge Injection in LLMs via Self-Distillation REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.226208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.226208Z digest=sha256:9a14881a8c82b05bff1de3aad10b2c29bf6ac03a6da463ac77c6893a3f4b9403

Observation ed94ebae-474a-4acb-a0d6-1e8c7e463793 · outbound

This paper cites InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining.

Efficient Knowledge Injection in LLMs via Self-Distillation InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.230237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.230237Z digest=sha256:3356d55fc9e898140d282cbb4af3df49b6983e390260fa594d0dd49a3a3b4640

Observation 6a66c2b8-fb06-43a0-8531-eda96ea69d6c · outbound

This paper cites In-Context Former: Lightning-fast Compressing Context for Large Language Model.

Efficient Knowledge Injection in LLMs via Self-Distillation In-Context Former: Lightning-fast Compressing Context for Large Language Model

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.234248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.234248Z digest=sha256:20a56cc761584ddaeee9b962ef84d5951e627d9d8f375f7dd9a05db7d2e563b8

Observation 923c68cc-4294-4dd4-a31e-c97c1eb74b92 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Efficient Knowledge Injection in LLMs via Self-Distillation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.238593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.238593Z digest=sha256:6c266a0bad153b59c89b9bc3fc0851397b72e05b52d7580926a18852c22f3ba5

Observation dbb9e362-91b0-48c8-ab4d-527e837e71b0 · outbound

This paper cites RAFT: Adapting Language Model to Domain Specific RAG.

Efficient Knowledge Injection in LLMs via Self-Distillation RAFT: Adapting Language Model to Domain Specific RAG

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.246602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.246602Z digest=sha256:704219fa30abb22c1698e4cf35f02503fe4145a714c15941a9810941cb879df6

Observation 41bedcf0-75ff-4798-ae30-f499cb4282e0 · outbound

This paper cites an unresolved cited work.

Efficient Knowledge Injection in LLMs via Self-Distillation Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-11T11:52:37.826001Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.250250Z digest=sha256:5cdd086fc4fa068622eae47d9d99841bd5ec0a9c5d97b7e28b4a6054236a36de

Observation 04e9f70e-b46c-466b-8655-729caef3457b · outbound

This paper cites C Related Work: More Detailed Review of Context Distillation In prior work, context distillation has been used for in-context learning and qualitatively modifying LLM behavior.

Efficient Knowledge Injection in LLMs via Self-Distillation C Related Work: More Detailed Review of Context Distillation In prior work, context distillation has been used for in-context learning and qualitatively modifying LLM behavior

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:52:37.811775Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.254877Z digest=sha256:4ccd65c1236ccf1a5d58f67060bf0212212f07330d81de13031646c230d86698

Observation 9cbae46e-8cd4-4a99-91cb-f11120cdc24f · outbound

This paper cites We found Bonito capable of generating competitive questions for the New York Times dataset.

Efficient Knowledge Injection in LLMs via Self-Distillation We found Bonito capable of generating competitive questions for the New York Times dataset

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:52:37.796868Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.258972Z digest=sha256:13a5ce7f8f4061ef0b94aa6db0fb8dd7030a6f1c27f4f6f1dd8eb5d424853d7f

Observation 9b9bc418-12e8-4212-bca3-54286de8d69b · outbound

This paper cites To explore potential factors underlying this phenomenon, we examine two key statistical properties of the teacher model’s outputs:.

Efficient Knowledge Injection in LLMs via Self-Distillation To explore potential factors underlying this phenomenon, we examine two key statistical properties of the teacher model’s outputs:

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:52:37.783268Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.262850Z digest=sha256:0e9e2050dbe5888e69f54b94fc39fe7301cca7a976220c4e4ca0fa90835796df

Observation 84748132-158c-4def-b593-fbe1bb9e97ad · outbound

This paper cites This characteristic may help explain why Llama-3- 8B-Instruct demonstrates superior performance as an expert compared to Qwen2.5-72B-Instruct (Table 3).

Efficient Knowledge Injection in LLMs via Self-Distillation This characteristic may help explain why Llama-3- 8B-Instruct demonstrates superior performance as an expert compared to Qwen2.5-72B-Instruct (Table 3)

Reference 42

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T11:52:37.766198Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.266686Z digest=sha256:06a7e4625bf8c420914cd5627ef89939a02114671dfd8679a73602efd237c882

Observation 241a108e-0ec2-4009-a715-e53238617d53 · outbound

This paper cites Splendid Cities.

Efficient Knowledge Injection in LLMs via Self-Distillation Splendid Cities

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:52:37.752900Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T11:52:37.270748Z digest=sha256:77c08a7247c4e55068a589491034a6f3b7d6d1d32d3ebb64e48b3e65232343d1

Observation 123ed824-d287-4346-b5ab-1066c915c06f · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Efficient Knowledge Injection in LLMs via Self-Distillation DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 2011

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.217777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.217777Z digest=sha256:dfe32ea053d30b330dacd0fcc644d455e19e8478ffda05e57a23a5a902fa8c0c

Observation f5475e12-fc41-4d5d-a90e-3e6d776adc2f · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Efficient Knowledge Injection in LLMs via Self-Distillation LoRA: Low-Rank Adaptation of Large Language Models

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.138767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.138767Z digest=sha256:bd790dfa4d2524034d86269c5187dd40984474e260589ffb30fe8a394baa2688

Observation 8b57b03b-a881-4fed-b327-2bbbb52cb362 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Efficient Knowledge Injection in LLMs via Self-Distillation Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.157917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.157917Z digest=sha256:900aec2e94d03b3bc3815080687803030a8c74baf6036cd8e10cd889a706b22c

Observation 54ab17d3-19ec-4103-9bdb-3bbfe2983a89 · outbound

This paper cites Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model.

Efficient Knowledge Injection in LLMs via Self-Distillation Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.242707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.242707Z digest=sha256:92f9ac83f33ded35dc3c08b51cae2aa402e640b3ac118f878b10d14e2f57cdd8

Observation 072dd78b-6d67-4811-a065-c09d41319785 · outbound

This paper cites Prompt Injection: Parameterization of Fixed Inputs.

Efficient Knowledge Injection in LLMs via Self-Distillation Prompt Injection: Parameterization of Fixed Inputs

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.108513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.108513Z digest=sha256:9291e747348112b128154779cb160045f7aaf5a283ea93622f92d953cf4e9b83

Observation 992cede1-a7a6-4848-b9c0-527f3f93f629 · outbound

This paper cites Revisiting Self-Training for Neural Sequence Generation.

Efficient Knowledge Injection in LLMs via Self-Distillation Revisiting Self-Training for Neural Sequence Generation

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.129494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.129494Z digest=sha256:d1a2afcfb0dded143747f23b94fb5e0aa0801d3674e6bfc00eaf8294f7d32846

Observation 3973a647-d213-43d5-a2d9-69ab10f3e25e · outbound

This paper cites Quantifying Memorization Across Neural Language Models.

Efficient Knowledge Injection in LLMs via Self-Distillation Quantifying Memorization Across Neural Language Models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.099890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.099890Z digest=sha256:90397406bbe6826d4fbb563da2e67cca0961669bad24aa724f7d2c9f2aa820fc

Observation 5740aedf-cc3a-4b95-bee8-5e89c618310e · outbound

This paper cites Language models are few-shot learners.

Efficient Knowledge Injection in LLMs via Self-Distillation Language models are few-shot learners

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.095907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.095907Z digest=sha256:7de22d9deafb30c923ce33fac8b884fae2fac3b720056432f872b6eb2629b16a

Observation 2a09967e-9457-49e0-a6fd-06aa0687e991 · outbound

This paper cites RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture.

Efficient Knowledge Injection in LLMs via Self-Distillation RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.121350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.121350Z digest=sha256:94ca1ed3b1b67b220fcda695deb4902852065de01d01bb89ee4ccdc134af30a8

Observation 28f18322-0f4e-4095-974c-ca52efd91650 · outbound

This paper cites A General Language Assistant as a Laboratory for Alignment.

Efficient Knowledge Injection in LLMs via Self-Distillation A General Language Assistant as a Laboratory for Alignment

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-11T11:52:37.091278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:52:37.091278Z digest=sha256:8b1b44fcb864a4256498841f9069054838aabc3cf01f6eb3ec4c2a616164e196

Pith citing papers

Observation f90dd867-10d9-4bb4-b121-883f62cffc77 · inbound

Cartridges: Lightweight and general-purpose long context representations via self-study cites this paper.

Cartridges: Lightweight and general-purpose long context representations via self-study Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:31.647548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:31.647548Z digest=sha256:fabb0d3102cb97b856c4ecbe3965c5605b64fd94d4bcb338f0630953c4bb531d

Observation e20039dd-2798-4308-8d3c-9870e2fd9dc7 · inbound

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe cites this paper.

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:26:16.201002Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-07T17:00:49.448352Z digest=sha256:e148f432110f593f0b2bc73d4542670297b24b2dafdaed8622d370525dbd0d4e

Observation fa696f57-f44a-4620-86a8-feb61f88b25c · inbound

Context Memorization for Efficient Long Context Generation cites this paper.

Context Memorization for Efficient Long Context Generation Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:43:12.658948Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-20T10:39:09.720412Z digest=sha256:c255caa3ad5c847fb2e52aa3bfa0d63e1b686331c8a67b234bd576006e64603a

Observation 30f0f7d0-80a4-4a18-96fd-14e643e083d5 · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:26:26.803207Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-28T10:56:13.058872Z digest=sha256:69e68b9d45a6aa580efc7a5056b1168137804a843e1365cbb1bbcd8bf138032a

Observation 9db19840-b7a8-45e5-9367-6f811e4c40c4 · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 77

Resolution
unresolved
no resolver link, observed 2026-07-13T07:44:25.325808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T07:44:25.325808Z digest=sha256:dbd4ed40be47413d21582eef6a46f247c8a277c21ac5f2329b6d7ee8356f4bbb

Observation 2cbc327f-02d1-47a7-90a5-93bd6eb5c31b · inbound

Rethinking Continual Experience Internalization for Self-Evolving LLM Agents cites this paper.

Rethinking Continual Experience Internalization for Self-Evolving LLM Agents Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 72

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T07:56:47.731556Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-28T06:29:11.398007Z digest=sha256:542135cc1dc5a40474c0f7c4da15306e2c789a35ff73f8c70e28a3de925ffb8b

Observation 0d92bd82-ed75-4d1e-914f-a3c13bc959a5 · inbound

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA cites this paper.

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA Efficient Knowledge Injection in LLMs via Self-Distillation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:45:42.802808Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-07-01T05:07:58.441326Z digest=sha256:faf9c20b2bdc8c119a2904fd8d453b965b4979ea539b71a986fb0b66eec8aa9c