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Paper Citation Record · LEDGER

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity

As of 15 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 4 inbound Pith citation observations for arXiv:2411.10069.

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

pith.paper-citation-record.v1
2411.10069 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:05:49.514611Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:42:46.597024Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T16:41:31.781711Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact1
  • verified fuzzy5
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b0ab721-1103-4d2e-a036-04268c59ce97 · outbound

This paper cites GPT-4 Technical Report.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.298836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.298836Z digest=sha256:775917d545966df2f6f14a94e874e2dd9d39c4888740c873164a8bf33031f3ca

Observation add81144-fa43-47d8-b8df-80f684438dad · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.336823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.304475Z digest=sha256:bafa417e808d4d31ee273964145230454325e440beb2c6b8b5495539cb3ef734

Observation 436de765-cffc-4bd4-afe1-46b3c1ecdb64 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.321329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.309302Z digest=sha256:512895268761fd565e03da8f82e3967e558b89c283afec1d8a2f4a03947c92f7

Observation 0296d905-7868-47a9-8d5d-799bd7942fb4 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.314294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.314294Z digest=sha256:38c868133f9e4c4e0d71bb16e5b5cfb6436c2f261b52ba098abe382dff45bcb1

Observation 3081a4fe-8649-4ce2-b234-1d7f47eeb152 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Constitutional AI: Harmlessness from AI Feedback

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.319731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.319731Z digest=sha256:99328c35e61cc9bdf754b2a81d60e6f9bdbfcf99f017ee6732afac1f8a55b374

Observation 96c76790-c756-46eb-b1e1-c4b1c201e488 · outbound

This paper cites Datasheet for the Pile.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Datasheet for the Pile

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.324883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.324883Z digest=sha256:456d85b96ce40cafae790564149744e340bf7e823c3dd02a5f595e15d5fde1c6

Observation 2e096131-485c-4884-a06b-9aef46571326 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.305787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.330428Z digest=sha256:20636afc7c8ac97d85191e914b3a13b6077b9b0dcfc731ebb66bc178713f41d9

Observation 06d47a20-927f-40b6-958a-eae3a7235541 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.290407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.335292Z digest=sha256:4344c8b2d69dd1d2a5850ff14f290da397330000d6ad67289534384781972eca

Observation 53ea4357-45dc-4ab0-97f5-2baa772b87cb · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.339938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.339938Z digest=sha256:b6b8b731cc4c9e6a63f10908f3f728144714a19afe2d980e9bd89e8de1c4bb7c

Observation 8cf1303c-bd96-47c4-bd51-7d71d6747662 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.263557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.344597Z digest=sha256:ca3e8d49f054d089cf43293eb8d03113726f976929d815d500a90520f7ce9988

Observation 85ab5eb2-1d64-44e5-8db2-8328350baf2b · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.246878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.349308Z digest=sha256:346d06f016d9773f951f9bf5e30fb8e015eabd86e1268138e292e891fa7ddc39

Observation 5f076433-4623-4565-8527-df6af9f817d6 · outbound

This paper cites Gonzalez, and et al.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Gonzalez, and et al

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:50.230192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.354235Z digest=sha256:3c5b92f21df24d023ee6507145f2b623620c754b8999806ae8992d9e32a4ae0d

Observation b234688c-8095-45d1-84af-e9d9de24dcae · outbound

This paper cites Glass, and Pengcheng He.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Glass, and Pengcheng He

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:50.212654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.358826Z digest=sha256:9a4d32573decd8e09876748a2111610ea56ebb6b8c9f3c8f9341249b69e268fb

Observation 0c4c1877-01aa-4c15-9f84-1d0e603ce90b · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.196728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.363645Z digest=sha256:fa3e48446841c9f3914af81eb590f294fd2108efc52b07062f3761080c3c8485

Observation f6f715fd-709a-4ea2-9536-a6905effb1d1 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.180588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.368359Z digest=sha256:3d39b8fa2ff4c8eb71f1fbd70c291322e1c39164f6d2392541765e19b96a2b8e

Observation 04f69d7e-137d-4d3d-8e69-7a888d559e19 · outbound

This paper cites Weinberger.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Weinberger

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:50.164731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.372964Z digest=sha256:c347e33b11d214e876118c9e13e924bfbcbec49818b37a37d8a527f088ade8e7

Observation a45d3b4f-b9ae-4400-9043-ea6e5aaf695e · outbound

This paper cites Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, and et al.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, and et al

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:50.148153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.377687Z digest=sha256:5f0391932f73f3fe017f7b90e129b47275ef9f9a81a8648c90dca9c999f7d571

Observation a38736c9-414b-4d88-aef2-2d0fbee532c4 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.382494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.382494Z digest=sha256:66f2b83788aa930cd4addaf1c91ecc69e97e74693f7b9e4e8ac2aa9bffff2a27

Observation f5a56edd-fc22-4458-86d2-eee8ca407af5 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.387375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.387375Z digest=sha256:0d8bd3e712bd354823fdfd1be078928c5126eb7d641cc4bef2ecdc762d970a38

Observation a5368972-6635-41a5-9530-de4a7c7b8e6e · outbound

This paper cites Language Models (Mostly) Know What They Know.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Language Models (Mostly) Know What They Know

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.392279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.392279Z digest=sha256:d8ecdab7ca50c7784f38447f2c62d1fc497056e93df6aabae4bb0381b5aeff97

Observation 29a952a5-da80-4967-9644-2eb3445330c2 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.397315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.397315Z digest=sha256:dd5f682562ae91508544d0c9ae0798e5ed764c346b2105474df883cff5a4de0d

Observation 5149736e-628c-447b-ad8c-a20db645edf5 · outbound

This paper cites Hashimoto.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Hashimoto

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:50.119651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.401908Z digest=sha256:2c43ce50cade17da3af7bcad3d62c68b0acda56fc1875ad34dbd79fe5450442c

Observation 5b605cb2-0c80-4b15-8b59-2e15623dc0b6 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.102986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.406588Z digest=sha256:b8bec45c8b1916a9a48a8aa28f1ce83632a8ec3c7f6fa0518a9ce40858bfd293

Observation 320c84d9-a52e-46df-8de4-5dede16eda58 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.086787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.411397Z digest=sha256:53ca4e0755e217b74a74fd38e8b0b51bb4b779d2d223c332941b3b1db6f08885

Observation 8eb33599-a3bf-4071-83e8-28b937dcced8 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.070760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.416190Z digest=sha256:71257ff06ab9155ef258ec995986fcf8d83fd42e2181d8a658f7ae528e274ab1

Observation 40d82a85-7a9d-4c7a-a637-a5868acbcd60 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.054824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.421015Z digest=sha256:eba5afc1d0d4f6376bf45e49664c7b47920f40a74dc999a8aca983ad680bc048

Observation 923754be-a1ae-4525-99ec-84e2c1e5d37a · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.425827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.425827Z digest=sha256:615d95afd1a024691c63e1636d0a2253d0c02dcc046373846e87ff162b4d5817

Observation 78d40262-c319-4844-8607-ff65dbc40fe1 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.028547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.430882Z digest=sha256:cd69cd008bb1a98fa43468bc4212db0f09ae0acaac77ebb7354f9b7dfa320a96

Observation 93544346-e49b-4d69-8ed9-d7fc978ca4c6 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.435593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.435593Z digest=sha256:277df1ba90254d1cee742d4194bbb13273c236f243f85e93ad371709304fc02c

Observation 5d69361a-b3e3-44fe-b87b-49f1978e2b53 · outbound

This paper cites Saarela and S.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Saarela and S

Reference 30

Resolution
verified exact
doi, observed 2026-08-12T20:05:49.555277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.440524Z digest=sha256:a61af2399687821951884683981fae3b5f468c906b5e1280983a9764db0d3132

Observation 408eede6-7f3e-4bba-9935-d703647660e0 · outbound

This paper cites Self-critiquing models for assisting human evaluators.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Self-critiquing models for assisting human evaluators

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.445270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.445270Z digest=sha256:b3ea01ee6c71824bf58ed4bb14f8063050deb571b7cd12e3878502d16aa7992f

Observation 75e83ebe-f9a9-4bf3-bad2-e47d088707ea · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:50.013036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.450228Z digest=sha256:cdc7f5b2580755beb83295b903a36822fe3ffedace9fbe6c0b56cf71ef0fe7d9

Observation ae6e5e22-263b-47e4-a9fb-268d4efefc0e · outbound

This paper cites Manning, Andrew Ng, and Christopher Potts.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Manning, Andrew Ng, and Christopher Potts

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.454949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.454949Z digest=sha256:e1f18ace4636982bcc4f34752fdae510d84db7948731f35150089c48a5a028e6

Observation a8f43d5e-bed4-4706-a65e-2d5b499cfad5 · outbound

This paper cites Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Models.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:49.459661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:05:49.459661Z digest=sha256:606d86168c0beed679be362cb7bc53dfd9ca5bf6d4d5b413175c2cdfd3d53465

Observation 7d09cdb5-17ba-428a-94f2-15a58dc3a3d5 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:49.987295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.464574Z digest=sha256:36e2c07e30e4da93c009ddc80869114a97dde4f07c9f8d445f7cfe9c3db05e44

Observation 096f12b7-5e21-4d86-bea3-e37d383d72c8 · outbound

This paper cites an unresolved cited work.

Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-12T20:05:49.971338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-12T20:05:49.469564Z digest=sha256:228c8c292e8664fcda4ab52b0526c7597eeef0e37a535137e8663db6b949ee66

Observation 4767945a-4df4-492b-b640-f8156b4148cd · outbound

This paper cites an unresolved cited work.

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Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity LLaMA: Open and Efficient Foundation Language Models

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Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

Reference 39

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Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Unresolved cited work

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Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

Reference 41

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Pith citing papers

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EM-MIAs: Enhancing Membership Inference Attacks in Large Language Models through Ensemble Modeling cites this paper.

EM-MIAs: Enhancing Membership Inference Attacks in Large Language Models through Ensemble Modeling Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity

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Correctness Assessment of Code Generated by Large Language Models Using Internal Representations cites this paper.

Correctness Assessment of Code Generated by Large Language Models Using Internal Representations Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity

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Observation a606eed4-3d3f-455d-a0f3-2437f4da66c5 · inbound

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization cites this paper.

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity

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Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization cites this paper.

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity

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