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Paper Citation Record · LEDGER

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective

As of 5 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2602.03396.

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

pith.paper-citation-record.v1
2602.03396 v3

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T08:17:14.427529Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:20:44.486147Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

  • verified exact9
  • verified fuzzy24
  • unresolved2
  • parse uncertain6
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3419b5a4-d48f-4289-9705-9b005bb52f19 · outbound

This paper cites Healai: A healthcare llm for effective medical documentation.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Healai: A healthcare llm for effective medical documentation

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.987658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:63064942646821e86665a090d5389c827c7e2d8eae01b5d0916c176514c46abd

Observation a855396b-9299-429b-9b08-2843f176b017 · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversation.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Autogen: Enabling next-gen llm applications via multi-agent conversation

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.981569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:d48e0d6affef1add47b2fee21d5b8d39f6a23976afd6929d274b02544b5e12fa

Observation 0b7fe16d-8d96-45d1-9638-f8782d8710bc · outbound

This paper cites Improving factuality and reasoning in language models through multiagent debate.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Improving factuality and reasoning in language models through multiagent debate

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.989750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:b55496cff04cdc931278c134d144557ef7ecf16ed8d7533587d3d4724e18d04f

Observation 6521d4e1-f20d-4541-b6df-032bc458b2a5 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Distilling the Knowledge in a Neural Network

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:17:36.150622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:c550a48b82cc77af37b71642cc628e701ab796bb648ca07602aa80d6031e8f4d

Observation 8374efb2-122d-4c41-ac5b-d5d5f678715f · outbound

This paper cites Sequence-level knowledge distillation.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Sequence-level knowledge distillation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.983760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:e3424dfa5197b641a55f39cc6fe4ff89a9a4376bf6c691739a0d4acb080f9516

Observation d33c244a-f188-4567-9b53-80b16d9e7760 · outbound

This paper cites Minillm: Knowledge distillation of large language models.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Minillm: Knowledge distillation of large language models

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.985737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:2d8b058598c36f54695ff074cccd79b695fd4013276f0a074a63d74c6d611fe0

Observation 61dad3d2-c860-45ba-b42e-58fcc25576c2 · outbound

This paper cites A watermark for large language models.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective A watermark for large language models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.992401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:1c65537cf1c71a1509a7d85acf3b4c3766440f616651887d360fd0f36da0777c

Observation 568777eb-7ba8-4c1d-acea-4a2cb8186363 · outbound

This paper cites Securing large language models: A survey of watermarking and fingerprinting techniques.ACM Computing Surveys.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Securing large language models: A survey of watermarking and fingerprinting techniques.ACM Computing Surveys

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.979610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:c3a2a70e410fee94a95974b719a8a1d67b18f4c81c0a0fd187b91dea3e633aa7

Observation 05507da6-a829-4af9-9506-602a09490ac6 · outbound

This paper cites Watermarking techniques for large language models: A survey.Artificial Intelligence Review.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Watermarking techniques for large language models: A survey.Artificial Intelligence Review

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.901960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:9ffd97e50a9c4d3d1d597c14699f7de49f174440c6edf9b5680f935847ea4c9a

Observation b9d5f715-5ae8-478f-87e9-c99ab73d5218 · outbound

This paper cites D-dae: Defense-penetrating model extraction attacks.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective D-dae: Defense-penetrating model extraction attacks

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.913072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:7310b37702bcc571ff1d4a04ee8d6b80baa240454ddce00a3367d6265aa48e07

Observation 8992a952-b3bb-476f-a1c1-07a9998ad8f0 · outbound

This paper cites Artificial fingerprinting for generative models: Rooting deepfake attribution in training data.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Artificial fingerprinting for generative models: Rooting deepfake attribution in training data

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.919106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:9d7ba1cf07f7423c7abf36d0be7bf770a7f6bea39f82027b1cb99b0224266c13

Observation d9bb8127-65ab-48f5-854f-f0e73a3c8b33 · outbound

This paper cites Fingerprinting deep neural networks globally via universal adversarial perturbations.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Fingerprinting deep neural networks globally via universal adversarial perturbations

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.955311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:b2adcfb9cdbd853c62b2662fe90c7b10ef0a2c63f2275e7c4efb0bd3fa50493c

Observation 9f3b2e77-2946-4cb5-bf42-349cc32f8715 · outbound

This paper cites Antidistillation sampling.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Antidistillation sampling

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:17:36.147768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:e9366cf38d2214f3619e8dae2fcc68038c7c216262f90423fe38a6995f78674d

Observation c6c331c8-e42c-4ec4-9862-5ae242891cb8 · outbound

This paper cites DOGe: Defensive output generation for LLM protection against knowledge distillation.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective DOGe: Defensive output generation for LLM protection against knowledge distillation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:17:36.128324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:3f6179405c2962690435cdc606f7c5d193ec8ad5cfb11138145c35653ac0b524

Observation 9d0fa617-4e8c-40f7-8074-79d77a15f845 · outbound

This paper cites Alphanet: Improved training of supernets with alpha-divergence.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Alphanet: Improved training of supernets with alpha-divergence

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.952431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:5a5209099218ea174fd899ff1aafddcaa22df997fc654963d025e83e1888585b

Observation a55f49b4-964a-4884-b635-857570d48ac9 · outbound

This paper cites Abkd: Pursuing a proper allocation of the probability mass in knowledge distillation via α-β-divergence.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Abkd: Pursuing a proper allocation of the probability mass in knowledge distillation via α-β-divergence

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.973251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:1565f3594638a24f61df4bb5576b52dd07da08f6768de1194abda4b71aec4f8d

Observation 143771c4-1a7d-47a5-8cec-0afcf6fc6ff4 · outbound

This paper cites Bayes conditional distribution estimation for knowledge distillation based on conditional mutual information.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Bayes conditional distribution estimation for knowledge distillation based on conditional mutual information

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.965066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:daea470d3ad5fc5582afd54a7950c14c7f613da106cd6a1d40f636f5eafc2e7b

Observation 3d06801b-9ad3-4b1a-8ef6-3213aef20c5a · outbound

This paper cites Opening the black box of deep neural networks via information.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Opening the black box of deep neural networks via information

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.967500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:1028e5d764a46d3dd932ee3e737225f8f443c77bc309701e408ed61eb6e122ef

Observation 6f5824aa-fcee-41d3-a0b2-55bb9445fa1e · outbound

This paper cites Instructional fingerprinting of large language models.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Instructional fingerprinting of large language models

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.960434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:bdee126f7b1f13b2197fc41bd41958c3c0b11c970ed5ded2c422c27b5ced872b

Observation 3f530dbd-9d23-48c7-8afc-1a782d17c7a3 · outbound

This paper cites The information bottleneck method.ArXiv.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective The information bottleneck method.ArXiv

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.971118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:4f1f9403686dbd0f37022b1568a6f984f71c47457a9caedfd46cb1baa4ca6f65

Observation ab3a6840-f041-4658-a2a8-68118c23db61 · outbound

This paper cites Deep learning and the information bottleneck principle.Information Theory Workshop (ITW).

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Deep learning and the information bottleneck principle.Information Theory Workshop (ITW)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.963019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:736475eafc40b971e5d6953f29a52335f0d6f31deff20f64aee554b294cef0ae

Observation 38753cc1-ddd9-440f-bd40-ec429619bf83 · outbound

This paper cites Alemi, Ian Fischer, and Joshua V.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Alemi, Ian Fischer, and Joshua V

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.975233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:4ef3da4bde51eb9ce45360b851a296379f28d99d5cc390c193d316d64ea77f74

Observation 767134fe-ea7a-4ec7-a175-954af281dbfa · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Lora: Low-rank adaptation of large language models.ICLR, 1(2):3

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.977620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:3f2d1bfa596397cb93a9bf83fef1eacea8564da22fd479cad9f32f7b7096ec2e

Observation deb549e6-7604-4a3e-a9bc-5252fe603b39 · outbound

This paper cites Qwen2.5 Technical Report.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Qwen2.5 Technical Report

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:17:36.144549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:5ecd289a1f9d614c15d147094d5f6e9966895014dbd15c87affb71fd65acf554

Observation c1773afd-538c-4038-bc84-e7f4c7641c91 · outbound

This paper cites The Llama 3 Herd of Models.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective The Llama 3 Herd of Models

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:17:36.124632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:345c9a3766a8a75f1152a63afa3595f00294ff4a6e61bab904fa166c27641e0f

Observation eb9c7c1f-621d-44fb-8dc7-0f8cec4dbda8 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Training Verifiers to Solve Math Word Problems

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:17:36.141356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:0dd45dedbb35df754f712561bf2948d51c59531a41abd135a91226bd472c6579

Observation 5c17180a-5d1e-41ac-af0e-d0c1a35cf361 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Measuring Massive Multitask Language Understanding

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:17:36.131618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:11a7f2f8127045f9cdd68a6cedb0ef7c72dec735de546386a40b16747c629aea

Observation 91842926-54fd-4b3f-af9d-624ae1a65822 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Measuring Mathematical Problem Solving With the MATH Dataset

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-05-16T08:17:36.134645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:219f1384171b0cb02c4de9de69d71b59f3e3f4e0b8c74802a0cf7ef4823bd222

Observation 195e1844-860d-45cd-b328-d02d01a5396e · outbound

This paper cites Tokenskip: Controllable chain-of-thought compression in llms.arXiv preprint arXiv:2502.12067.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Tokenskip: Controllable chain-of-thought compression in llms.arXiv preprint arXiv:2502.12067

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:17:36.138077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:d57e4f04416107e300814c60e82c49c7f70011ba989ca94dd000b277efe5ea89

Observation 8dc2d01d-ac45-4a5b-9bac-3585bed3c448 · outbound

This paper cites Let’s verify step by step.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Let’s verify step by step

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.941620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:afd11e995fb5f3d006f7f4ab2e3dd75c2a16cbeb701a84d9afa37774345f0785

Observation 31e26d52-6e65-468d-9323-92b625676b0e · outbound

This paper cites Distillm: Towards streamlined distillation for large language models.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Distillm: Towards streamlined distillation for large language models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.933222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:8d373633b0570d0e7cb018a3fcf22cf3b5d217d196457ccce54ab194131bc372

Observation dce361bb-10c8-4079-912b-2dbb99200243 · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-05-16T08:17:36.936123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:c53189b3ee301f0a44172b5f529c45430605c327d92a2ed468ab07b97785acdf

Observation a9fe66d5-b618-4c8c-86e7-c2deec3248d9 · outbound

This paper cites Don’t repeat the question.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Don’t repeat the question

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.930127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:32280fc79db457ea07951a016dfe7f28ee8c629245c967843544ab94ca23a1e4

Observation 8daba266-f631-46d2-82f5-7261c22a20a9 · outbound

This paper cites using someone as a mere means.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective using someone as a mere means

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-16T08:17:36.916137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:dd0f38a6524623e2496ce3aa8d7f5d4f2df15a33a3bcf3d0f8cb56a763d3897f

Observation e0f04018-86d9-442c-b1b4-5f1b1d9972af · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 35

Resolution
parse uncertain
raw_fallback, observed 2026-05-16T08:17:36.945499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:073d4908334178fe8f11615b735e1d69a14f6ecacda506462088a9d3683f6bce

Observation 624cd70f-17c7-4660-b9c3-2abcc78b1d2a · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 36

Resolution
parse uncertain
raw_fallback, observed 2026-05-16T08:17:36.957893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:eef099a51e65031f1d768c9ac2e5a27545bb28d7af3359a035759091f6db6cd8

Observation a3860dbe-0d6e-4877-9791-05d336670110 · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 37

Resolution
parse uncertain
raw_fallback, observed 2026-05-16T08:17:36.921874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:f49ba11364e9cde487298dd174341a7f0d643b951097dee18627996009831db4

Observation 1aea6491-ff73-4223-bcf1-908f4112cb54 · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 38

Resolution
parse uncertain
raw_fallback, observed 2026-05-16T08:17:36.926148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:3479fb39307635b875abb6585646acd32022751daa871fd923ee61ffc8a47736

Observation c915ea52-b6eb-4d6a-80d0-f7703c91c524 · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 39

Resolution
parse uncertain
raw_fallback, observed 2026-05-16T08:17:36.948729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:49a886a2a2992f5fa19aea514a8aa2cdd146d55f81e874bd509bd0c768455f33

Observation 63d0dc74-08b4-4d6c-8819-647a5e312a4d · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 40

Resolution
parse uncertain
raw_fallback, observed 2026-05-16T08:17:36.906148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:0cdeafd5f164b15498579d0c855aaf5894b508e23e3b27f194cedf7e0fe6fca2

Observation 48e36357-5cc0-48b4-8e10-0fd7c935230c · outbound

This paper cites an unresolved cited work.

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-05-16T08:17:36.909470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:17:14.427529Z digest=sha256:9d4da0c4a888a0707788619aa65b29f277ed3d3d7421c395feef27d2176d14dd

Pith citing papers

Observation 846a3e29-f40e-4e7f-86bf-38238ced16d9 · inbound

ADS-C: Antidistillation Sampling for Classification cites this paper.

ADS-C: Antidistillation Sampling for Classification Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-01T23:20:44.486147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:20:44.486147Z digest=sha256:7ab0f1de45807b48290a008037a6d940335c38c05c6d7e9e86c9a0792fbff60e