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Paper Citation Record · LEDGER

On Teacher Hacking in Language Model Distillation

As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2502.02671.

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

pith.paper-citation-record.v1
2502.02671 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:34:57.198738Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:45:03.331296Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:45:05.037045Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2b76f6bd-3f57-457b-b833-4f55e15c42d3 · outbound

This paper cites an unresolved cited work.

On Teacher Hacking in Language Model Distillation Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T11:34:57.198738Z digest=sha256:1779e78432a54089776bfa5891318b08fba41c3b53c6331477647cae09caede1

Observation 960a8d90-3a91-4eda-aa8c-1c3ba9f7958d · outbound

This paper cites Unsolved Problems in ML Safety.

On Teacher Hacking in Language Model Distillation Unsolved Problems in ML Safety

Reference 7

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source=pdf_text observed=2026-08-09T11:34:56.920640Z digest=sha256:473915fbee8b9fcb69c49f50fcfb157ac4e4bcca7f97cd53a653c7c3b141353f

Observation 9318d52b-f9ce-4aaf-9865-f47d734a62cd · outbound

This paper cites Sequence-Level Knowledge Distillation.

On Teacher Hacking in Language Model Distillation Sequence-Level Knowledge Distillation

Reference 11

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source=pdf_text observed=2026-08-09T11:34:56.942721Z digest=sha256:36f887e10cac450396643fdf83c017fe2a0dedc1fb3a686cae9159023d0c76c5

Observation 3d4cb55c-6109-4502-8d33-b59771de9ca1 · outbound

This paper cites Autoregressive Knowledge Distillation through Imitation Learning.

On Teacher Hacking in Language Model Distillation Autoregressive Knowledge Distillation through Imitation Learning

Reference 12

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source=pdf_text observed=2026-08-09T11:34:56.975671Z digest=sha256:2b87d1cfe5259c0f8f194f94d204818fff31147d2b9357275330300ab2ea2d6b

Observation 380e2e34-d2b9-4b37-8a5c-2a7648de7c00 · outbound

This paper cites DeepSeek-V3 Technical Report.

On Teacher Hacking in Language Model Distillation DeepSeek-V3 Technical Report

Reference 13

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source=pdf_text observed=2026-08-09T11:34:57.012110Z digest=sha256:9cb7f75e693d43b79f9a3959f0b9cf11af49b644ac4f69be3e84e0af647e3fe3

Observation 2ae105ab-7403-4dea-80d8-168ec22821ea · outbound

This paper cites B., and Lapata, M.

On Teacher Hacking in Language Model Distillation B., and Lapata, M

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:34:57.640894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T11:34:57.042852Z digest=sha256:6cdafde0734dae6d840903805071146595fe03a762bd07b7e999261d5bc69e0f

Observation a9d1e721-e2b8-4dc9-95e0-c08bbe5ec341 · outbound

This paper cites The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models.

On Teacher Hacking in Language Model Distillation The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models

Reference 16

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source=pdf_text observed=2026-08-09T11:34:57.100873Z digest=sha256:fc2440049cb4c9ff2a938aefcfcdc7ddbe0132e98411d2d980c271a2d633c060

Observation b8af2d07-08a3-4725-832d-7f275034c4bd · outbound

This paper cites Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms.

On Teacher Hacking in Language Model Distillation Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Reference 17

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source=pdf_text observed=2026-08-09T11:34:57.128745Z digest=sha256:dcaf04da1f0ae2413ea6681ba43187d488b85b37bc35644fd413769439cef16d

Observation a9917ce7-d6d8-45b9-a5cf-cfb28070d176 · outbound

This paper cites WARM: On the Benefits of Weight Averaged Reward Models.

On Teacher Hacking in Language Model Distillation WARM: On the Benefits of Weight Averaged Reward Models

Reference 18

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source=pdf_text observed=2026-08-09T11:34:57.150732Z digest=sha256:69435a6b94fe392dd17b686b890415add9f013bbf02eb9f417442c21c611f865

Observation 742b1719-657f-4cad-91f1-eb939d2eaeec · outbound

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

On Teacher Hacking in Language Model Distillation Gemma 2: Improving Open Language Models at a Practical Size

Reference 19

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source=pdf_text observed=2026-08-09T11:34:57.156496Z digest=sha256:4dfdd711a83f5cddc43ccfc4727d41b907aa095d70f0d80d3bddfd3e9c0609a7

Observation 2ff5f2db-b2b4-4252-a7d6-66a689e57f8c · outbound

This paper cites Scaling Up Models and Data with $\texttt{t5x}$ and $\texttt{seqio}$.

On Teacher Hacking in Language Model Distillation Scaling Up Models and Data with $\texttt{t5x}$ and $\texttt{seqio}$

Reference 21

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source=pdf_text observed=2026-08-09T11:34:57.167515Z digest=sha256:4fc195b01af1060c179703690d191100537d35d6ea77877dcac9e43ffe9a7522

Observation 4841ee5f-8954-4e5f-94d9-926bbc1fbbe3 · outbound

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

On Teacher Hacking in Language Model Distillation DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 22

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source=pdf_text observed=2026-08-09T11:34:57.172471Z digest=sha256:f9cddfa68b2d2dae81c8a3808d22cbe619ea30cba4dba19edefffdf68c968fa1

Observation 65b7cce2-5efb-4116-b854-1d57b5fe6d9a · outbound

This paper cites Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation.

On Teacher Hacking in Language Model Distillation Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation

Reference 25

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source=pdf_text observed=2026-08-09T11:34:57.189016Z digest=sha256:fad6d629833c9db7952fb02b106ef429015d332bd3b87bcf07b4b0bf661e0b61

Observation 175fecbf-e0a5-48ed-8931-99fe2d20241d · outbound

This paper cites an unresolved cited work.

On Teacher Hacking in Language Model Distillation Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-09T11:34:57.624594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T11:34:57.194274Z digest=sha256:bfd787239c00c01e635ded726d8dd8004c15cec6842a6860fe38fe0ca38c5f94

Observation 644c30ee-7652-440f-8220-041e2483eada · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

On Teacher Hacking in Language Model Distillation Zephyr: Direct Distillation of LM Alignment

Reference 1997

Resolution
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no resolver link, observed 2026-08-09T11:34:57.178509Z

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source=pdf_text observed=2026-08-09T11:34:57.178509Z digest=sha256:5eca385669b7b872fc8ad4881f1e755c139d0200c226c9d09944b0f20653ad41

Observation a2d964af-fd96-4424-8667-bbc72aba3a2b · outbound

This paper cites ODIN: Disentangled Reward Mitigates Hacking in RLHF.

On Teacher Hacking in Language Model Distillation ODIN: Disentangled Reward Mitigates Hacking in RLHF

Reference 2006

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source=pdf_text observed=2026-08-09T11:34:56.907788Z digest=sha256:4f9b92438c19939f0f768c232a1bc4ac3e4d4a1d4db925c97d67b4007fd6a22f

Observation 04bdcc2c-96f8-48f9-adb2-c35da20ea704 · outbound

This paper cites doi: 10.3115/v1/W14-3302.

On Teacher Hacking in Language Model Distillation doi: 10.3115/v1/W14-3302

Reference 2014

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source=pdf_text observed=2026-08-09T11:34:56.901841Z digest=sha256:1503ef5e22cbd1363e7be7afcaf726c0feaf0e39e9c47a57fa7c6dfad01c0733

Observation b2f779b1-5788-41e3-a593-46cebc98585b · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

On Teacher Hacking in Language Model Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 2015

Resolution
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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:34:56.926817Z digest=sha256:fe9e615d2cc111eded6dfaef2d4698942222b49fe5d15fa6884d03a9363b0e9c

Observation d2140783-1c12-4353-84c9-6e64a19afbdb · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

On Teacher Hacking in Language Model Distillation Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2016

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source=pdf_text observed=2026-08-09T11:34:56.890311Z digest=sha256:efd6e39636b62b5f178db00714c69568ddc3537121d01061ce0e627fd91c3b54

Observation a4c2bbc3-3adc-4e7f-b305-b9f914a969ac · outbound

This paper cites doi: 10.18653/v1/D18-1206.

On Teacher Hacking in Language Model Distillation doi: 10.18653/v1/D18-1206

Reference 2018

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source=pdf_text observed=2026-08-09T11:34:57.071170Z digest=sha256:628e4f4a12d5010c57c9b86f658268cc8e4e460c0187fe822b970e738a01feda

Observation e3446707-e7f7-4986-9c56-b33813e27238 · outbound

This paper cites Scaling Laws for Neural Language Models.

On Teacher Hacking in Language Model Distillation Scaling Laws for Neural Language Models

Reference 2019

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source=pdf_text observed=2026-08-09T11:34:56.932470Z digest=sha256:a61dcb0cbc576ad949d677f77b9599514a369bd9d7323a8695f11afbb48239ac

Observation 5079aeb4-3010-4a7a-b30e-1bacc08cb956 · outbound

This paper cites PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning.

On Teacher Hacking in Language Model Distillation PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning

Reference 2020

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source=pdf_text observed=2026-08-09T11:34:56.937688Z digest=sha256:d3d9c6bf8593db1087ab5becb881f38ef779e1089d6b16df6b2ae949188a08f6

Observation bf2cbe1c-3a37-4d91-9527-518e6f543717 · outbound

This paper cites Language Models Learn to Mislead Humans via RLHF.

On Teacher Hacking in Language Model Distillation Language Models Learn to Mislead Humans via RLHF

Reference 2021

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source=pdf_text observed=2026-08-09T11:34:57.183913Z digest=sha256:eda81405563e2e7914c9201d2122d33a51c84737f34b86fa72ae14a2084bf95d

Observation e5037d20-7ab6-4d33-8ca2-542aea9cc5b3 · outbound

This paper cites Findings of the 2014 workshop on statistical machine translation.

On Teacher Hacking in Language Model Distillation Findings of the 2014 workshop on statistical machine translation

Reference 2022

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raw_fallback, observed 2026-08-09T11:34:57.658851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T11:34:56.896299Z digest=sha256:0434f196f4adcedc8dbdb3cda614037956c03e42f0207145a6149bb5e61ac01b

Observation be93f680-b27a-4f21-985b-94a377288f4a · outbound

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

On Teacher Hacking in Language Model Distillation Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 2023

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source=pdf_text observed=2026-08-09T11:34:56.914050Z digest=sha256:deaf218a098617dd5b30a4cd7961e3b7d9b7b7dcaf72eaea85d208131472bdec

Observation 867258ab-a084-4776-b325-c25c5abea41e · outbound

This paper cites Concrete Problems in AI Safety.

On Teacher Hacking in Language Model Distillation Concrete Problems in AI Safety

Reference 2024

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source=pdf_text observed=2026-08-09T11:34:56.883725Z digest=sha256:b1d35103f9bb41d5d43fc46457d7fe959bfbe64549217558323db3e1cb26ac1b

Pith citing papers

Observation 8a34b152-2464-440c-a5d0-9a7c4e36895b · inbound

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

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation On Teacher Hacking in Language Model Distillation

Reference 46

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local_arxiv, observed 2026-08-06T22:45:05.113351Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T22:45:03.331296Z digest=sha256:a54f12fed5a09994fd9932645d2859e163326f1d91b12223f15291960c0c33b2