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Paper Citation Record · LEDGER

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?

As of 17 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2505.12871.

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

pith.paper-citation-record.v1
2505.12871 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:31:40.421300Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T02:14:38.644041Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:16:57.384201Z

Reference resolution

58 of 58 outbound references displayed

  • verified exact3
  • verified fuzzy10
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f68d2ef-22b1-48ae-8ca2-f00beb7a1e95 · outbound

This paper cites write newline.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? write newline

Reference 1

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no resolver link, observed 2026-08-15T20:31:40.003425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.003425Z digest=sha256:8a79bae906a902809f64d7d02a0f4da29d8e058e29d8182e3914be1855e51924

Observation bd8f583d-ab24-4849-b338-c89992e7a2e1 · outbound

This paper cites Intrinsic dimensionality explains the effectiveness of language model fine-tuning.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Intrinsic dimensionality explains the effectiveness of language model fine-tuning

Reference 2

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no resolver link, observed 2026-08-15T20:31:40.009597Z

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source=arxiv_source observed=2026-08-15T20:31:40.009597Z digest=sha256:182d311d1566d1926c3936de44ec76a2fe19989d35a45f49c0a419efb9823c9b

Observation 451ec35e-a718-48c7-937e-c031105c99ea · outbound

This paper cites Information geometry and its applications, volume 194.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Information geometry and its applications, volume 194

Reference 3

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no resolver link, observed 2026-08-15T20:31:40.017850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.017850Z digest=sha256:9380cf54b9f560ae8b087372086dd747f17830fb6f9b08d55f3a42df44fe5af4

Observation d94c2c9d-7617-42d7-aad1-576ada46ca21 · outbound

This paper cites On Exact Computation with an Infinitely Wide Neural Net.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? On Exact Computation with an Infinitely Wide Neural Net

Reference 4

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no resolver link, observed 2026-08-15T20:31:40.024566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.024566Z digest=sha256:63b7d278609e8422496d0d1206472cc64ac8bf08eac767652585c5c3b0708ab7

Observation d0d105d2-5e8d-48e7-89e1-b147bc538e99 · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 5

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no resolver link, observed 2026-08-15T20:31:40.031565Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.031565Z digest=sha256:fa7281428714de3f798e3588ca157709a5338641fbd74402d7aeeeabc0dd9aed

Observation 4599d7de-b644-4b30-8bf9-1485d0290309 · outbound

This paper cites C., Roxo, T., Proença, H., and Inácio, P.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? C., Roxo, T., Proença, H., and Inácio, P

Reference 6

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no resolver link, observed 2026-08-15T20:31:40.037516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.037516Z digest=sha256:5da4e79aebd064297f9b88033c34700837b3a46af6c1881776baabbbe23bcde5

Observation e51acadd-8d99-408c-8f02-62db70e5903e · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 7

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no resolver link, observed 2026-08-15T20:31:40.043571Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.043571Z digest=sha256:d4fecd4243136809a3ef85c5615c69d5cdac2cfb3132816a55be47c0fb47eb63

Observation c46d07f0-0708-4be2-8131-4afb42d860a6 · outbound

This paper cites an unresolved cited work.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Unresolved cited work

Reference 8

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raw_fallback, observed 2026-08-15T20:31:41.877980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.053476Z digest=sha256:efecf27527145be70f2a20c89052a288f34cad128da9fe888c75d15934e20d8a

Observation 6d094f72-a882-49bd-ab85-ba77aab4028f · outbound

This paper cites A survey on data poisoning attacks and defenses.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? A survey on data poisoning attacks and defenses

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.065880Z digest=sha256:74be8560ce8f7ff17fba107f6268ad1e1bde4fe0058ed4ab7bc4e4015b6797c3

Observation b933eb05-d82a-45a7-80a9-15d329cd9334 · outbound

This paper cites an unresolved cited work.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.071241Z digest=sha256:1d62f05a227843ddd351ea900be0643435d68801e5fd186e5f04b10ddb0d03a6

Observation 9c4378d3-587a-4431-8a2f-40e99566ebb6 · outbound

This paper cites BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 11

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source=arxiv_source observed=2026-08-15T20:31:40.083693Z digest=sha256:6db8e0f7e515bb27f261dcb6bd62eeb868a18fc6eeef74a2cda373c7fd0648d2

Observation cf68e903-38a6-43cb-bbed-9e788506730e · outbound

This paper cites an unresolved cited work.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-15T20:31:40.097848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.097848Z digest=sha256:23d4377a7b0a504f5881b76e1fc1f32a8ec497832e294655e0199d862b49a562

Observation b9e97e47-5173-4c3c-828c-9fb8e7a6c202 · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 13

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no resolver link, observed 2026-08-15T20:31:40.103246Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.103246Z digest=sha256:d421fbafcfb5da7528bd40c6921760c4f6e532a656e9508e2ff6dc7dcf0e4a0b

Observation e915e485-cfed-403f-a0db-d13fd0af1a48 · outbound

This paper cites The Impact of Initialization on LoRA Finetuning Dynamics.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? The Impact of Initialization on LoRA Finetuning Dynamics

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.111313Z digest=sha256:b0a93a503c58e1318de32bad89d0dd5f070ac84c6027fac08e11a324d1630d12

Observation 10514266-06ad-44e7-b016-92f07e0c03db · outbound

This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Reference 15

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no resolver link, observed 2026-08-15T20:31:40.120329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.120329Z digest=sha256:10e410b1752d5eb9fa1bf27b1d083a410b7570ad2cd51aa9753cfe68e3b26c9a

Observation ed460a33-6ac9-4c54-9fb4-9bc19fbdbfa2 · outbound

This paper cites Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs

Reference 16

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verified exact
local_arxiv, observed 2026-08-15T20:31:41.194301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.127107Z digest=sha256:da9661bc23ec9a3fd9dea06ac7d79bcff534bb9091207bdaa54636265e69d326

Observation ceb8cf43-3bca-48fc-a8fc-5dab04684add · outbound

This paper cites Recovering the pre-fine-tuning weights of generative models.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Recovering the pre-fine-tuning weights of generative models

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.815699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.133775Z digest=sha256:3ffc5933956f63fce9641224d7b29cea8f2f5cbcdc6e52b6d00797fa918bd406

Observation 3dc3616d-69a0-45aa-af35-6a428421779e · outbound

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

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? LoRA: Low-Rank Adaptation of Large Language Models

Reference 18

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no resolver link, observed 2026-08-15T20:31:40.141697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.141697Z digest=sha256:a3aa886bdcc3bb7a838bbcd776616465cb9b2f29ac34bc990d4eb401edf72fd3

Observation 56b3c27c-fe2f-4bfe-b554-57db2f9366f8 · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 19

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no resolver link, observed 2026-08-15T20:31:40.148984Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.148984Z digest=sha256:2701377afcc41e903d831aabcf457934a5f8000d6af19b8a11f39b4f64aa8185

Observation dc7d0436-62b7-45ed-846e-cf73f264d6d1 · outbound

This paper cites Neural tangent kernel: convergence and generalization in neural networks (invited paper).

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Neural tangent kernel: convergence and generalization in neural networks (invited paper)

Reference 20

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metadata mismatch
raw_fallback, observed 2026-08-15T20:31:41.151699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.156906Z digest=sha256:7ca46e1020cc420294fbdd71d016905f4a8c9297368bfd85f07a08294e417823

Observation 84611502-3626-46cc-a311-48fe710e16e7 · outbound

This paper cites D., and Ryu, E.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? D., and Ryu, E

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.780429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.166201Z digest=sha256:3baefe4a46055367952b50e931dfd349eca9ea02c3b98319d1b8aef983d7e35d

Observation 401fefe9-d26a-4dd9-bf8a-05307f04bbfb · outbound

This paper cites Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.174758Z digest=sha256:aa7e53ab7a41231ebb9c55fc84e13c8ec740b897f6012d0fdf12310641a01420

Observation ca06b02c-185f-4489-8003-3e783494324f · outbound

This paper cites Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics

Reference 23

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no resolver link, observed 2026-08-15T20:31:40.179160Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.179160Z digest=sha256:791ef54310aadf5f3bd5736937d8eb31578d02f8dcbdd7244bdb142fd0864741

Observation 2747d6c1-bb89-4b44-afca-9dee3847d840 · outbound

This paper cites On weight initialization in deep neural networks.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? On weight initialization in deep neural networks

Reference 24

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no resolver link, observed 2026-08-15T20:31:40.184329Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.184329Z digest=sha256:6de58cdd9d536855d0367216a58c52e38d234dceccc587207470a31001f81405

Observation ce103f1e-8184-4bfd-8119-ce0966d38f87 · outbound

This paper cites S., Pennington, J., and Sohl - Dickstein, J.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? S., Pennington, J., and Sohl - Dickstein, J

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.753388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.192480Z digest=sha256:d770a604718b7c262298e2e938dba165e0e03e46d1fd7600edef151ed7ac1cec

Observation 63990f17-e8c4-4497-b597-7a934aaa0b3f · outbound

This paper cites BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks and Defenses on Large Language Models.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks and Defenses on Large Language Models

Reference 26

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no resolver link, observed 2026-08-15T20:31:40.198074Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.198074Z digest=sha256:715dd12b66c63d4e7e1c273d48f179236aeb4eb00d1cb1b85ca954bccd08944b

Observation 5a92ea35-1900-456a-b155-2e30442f8f10 · outbound

This paper cites "Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced Distillation.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? "Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced Distillation

Reference 27

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no resolver link, observed 2026-08-15T20:31:40.205514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.205514Z digest=sha256:426b3e5f1354951e47d3931e7267d2a1f918d3d610c90fcddb5a34345e19e4a9

Observation 1ab08c27-4ebc-4e2d-a38a-10d7629473b8 · outbound

This paper cites LoRATK: LoRA Once, Backdoor Everywhere in the Share-and-Play Ecosystem.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? LoRATK: LoRA Once, Backdoor Everywhere in the Share-and-Play Ecosystem

Reference 28

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unresolved
no resolver link, observed 2026-08-15T20:31:40.215198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.215198Z digest=sha256:6e9736a9717ab23107100dc365af334f12d903e820793380d24f836a29c7d93f

Observation 854916e0-5558-43f2-af6f-7a97f169df3a · outbound

This paper cites A kernel-based view of language model fine-tuning.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? A kernel-based view of language model fine-tuning

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.732655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.221221Z digest=sha256:83e9384c5b116428720df3e9bfeff1543de27aaada43be23532fb31364cca0f6

Observation b9afb5c1-b466-44a9-a912-aa8b1cdcf5b2 · outbound

This paper cites Peft: State-of-the-art parameter-efficient fine-tuning methods.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Peft: State-of-the-art parameter-efficient fine-tuning methods

Reference 30

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no resolver link, observed 2026-08-15T20:31:40.226360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.226360Z digest=sha256:71b659f8814c96c8bcc259cbc20dafbcc3c29f7e52a64f342b160ec71e98d8ee

Observation a96d1a89-3a34-4f3b-94f2-eca1baaf6e18 · outbound

This paper cites A Survey on LoRA of Large Language Models.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? A Survey on LoRA of Large Language Models

Reference 31

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no resolver link, observed 2026-08-15T20:31:40.231727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.231727Z digest=sha256:11b48e0bd742e3e6a68ea620f87175327eadce6c0df39d43be7f436d1cad59f4

Observation 964a4fc6-836e-4753-9c53-e650537a0033 · outbound

This paper cites An information geometric perspective to adversarial attacks and defenses.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? An information geometric perspective to adversarial attacks and defenses

Reference 32

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no resolver link, observed 2026-08-15T20:31:40.236737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.236737Z digest=sha256:9dfcbae50a789916b010602072a0116e161a3152e1ed46d7d5c514c7cf90cc6c

Observation 032f9920-57ec-468c-ab81-21a8e471e28b · outbound

This paper cites An elementary introduction to information geometry.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? An elementary introduction to information geometry

Reference 33

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no resolver link, observed 2026-08-15T20:31:40.241713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.241713Z digest=sha256:d7f7d81305b266749125686cf01a38845c67ffb24b1d7e3a4c3440478f5c882c

Observation b819b5dc-0e3c-4dbd-a66d-757b60ec9b58 · outbound

This paper cites Hidden trigger backdoor attack on NLP models via linguistic style manipulation.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Hidden trigger backdoor attack on NLP models via linguistic style manipulation

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.690621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.247124Z digest=sha256:777d59cedc6d475d48e273a5ab21e9340d340871ced107d9111d561c9705b5be

Observation 3ee1022e-0b79-4793-852a-817f861a6625 · outbound

This paper cites A survey on recognizing textual entailment as an NLP evaluation.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? A survey on recognizing textual entailment as an NLP evaluation

Reference 35

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no resolver link, observed 2026-08-15T20:31:40.254564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.254564Z digest=sha256:b6c6d9f594c24c4319e4bd00aeed32fd7d68effb5da94f4ed632b5e6dace7e18

Observation 2cde813d-02eb-4928-bee8-49c227252366 · outbound

This paper cites Geoda: A geometric framework for black-box adversarial attacks.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Geoda: A geometric framework for black-box adversarial attacks

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.672716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.260956Z digest=sha256:b4e5545a48d15fdb0c2966f276ab4bb8c9ed85730eed3223a88dee988ba9c4dd

Observation 3541e524-4e04-407b-96d1-69998e4299e1 · outbound

This paper cites Poisoning Attacks and Defenses on Artificial Intelligence: A Survey.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Poisoning Attacks and Defenses on Artificial Intelligence: A Survey

Reference 37

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source=arxiv_source observed=2026-08-15T20:31:40.267521Z digest=sha256:c0b488b2f974001d48a4b80f357b41398a4e4923e6d6b4a6262a6f70c97d7cc8

Observation 5183edaf-62d5-4330-b490-0a60851a6385 · outbound

This paper cites On measures of entropy and information.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? On measures of entropy and information

Reference 38

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no resolver link, observed 2026-08-15T20:31:40.274444Z

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source=arxiv_source observed=2026-08-15T20:31:40.274444Z digest=sha256:3c2c288f31770e5096d7bf2805eb93ffc999a17c2202f80f6bd2b82dde033256

Observation 0ba3793a-c01b-4246-9eae-5f65175a858f · outbound

This paper cites Natural Language Understanding with the Quora Question Pairs Dataset.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Natural Language Understanding with the Quora Question Pairs Dataset

Reference 39

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no resolver link, observed 2026-08-15T20:31:40.280603Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.280603Z digest=sha256:b2fab065a7a2ec5a30cb79894152f962599bfb8423eeb49f78be2189aa09252f

Observation 991a70b4-d1ff-479d-af4a-eab24860c78f · outbound

This paper cites D., Ng, A., and Potts, C.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? D., Ng, A., and Potts, C

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.634888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.289449Z digest=sha256:c5f47a55bb6df615a34f7aea84423b5a280558b2ed60f72cebcd6b880d7a81ed

Observation 860b5a6b-c136-4a90-9681-6dfdf3851c27 · outbound

This paper cites an unresolved cited work.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Unresolved cited work

Reference 41

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source=arxiv_source observed=2026-08-15T20:31:40.295243Z digest=sha256:e550c4f959460483915895104813cc6510656c5545f44272c5dc0e077aa80748

Observation 9104df47-dd76-4e3e-a8b8-26580b35c647 · outbound

This paper cites Attention is all you need.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Attention is all you need

Reference 42

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no resolver link, observed 2026-08-15T20:31:40.300382Z

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source=arxiv_source observed=2026-08-15T20:31:40.300382Z digest=sha256:ec212b569c4b94d9e8d23eec93d52a1df64b21e418c2f87f3074f478383f0b30

Observation de9b6d39-5597-4ccc-ae28-d510c4cc62cd · outbound

This paper cites Poisoning language models during instruction tuning.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Poisoning language models during instruction tuning

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.565093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.305858Z digest=sha256:1a3c1d1eadfa2d8fc5bda0be666100b00c6aa4ff0e35646563aed8ec0d573c32

Observation 09c92add-a23f-4d18-bc45-2a71b520571b · outbound

This paper cites GLUE : A multi-task benchmark and analysis platform for natural language understanding.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? GLUE : A multi-task benchmark and analysis platform for natural language understanding

Reference 44

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no resolver link, observed 2026-08-15T20:31:40.316258Z

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source=arxiv_source observed=2026-08-15T20:31:40.316258Z digest=sha256:05c7646eee8add2ad05dd2f1a5f71a42663103eeea4f27fc072f581654044f1c

Observation b8721272-7c37-4ab3-b046-73de7342edb0 · outbound

This paper cites Lora meets dropout under a unified framework.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Lora meets dropout under a unified framework

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.534593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.322400Z digest=sha256:33ebcec3f72ab72a39e83f6895f12fadda134bf5f6acb472bf315a7574cf5b6f

Observation 88f5d498-909c-4033-b822-b84d8f3195ca · outbound

This paper cites New Paradigm of Adversarial Training: Releasing Accuracy-Robustness Trade-Off via Dummy Class.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? New Paradigm of Adversarial Training: Releasing Accuracy-Robustness Trade-Off via Dummy Class

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:31:40.911553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.327761Z digest=sha256:b1d18eeb67fe0de243456029429b10e7e7cf46fa01508024354629c5f51cd39c

Observation 516e593b-35b5-4d4e-8022-29ea2b71cb22 · outbound

This paper cites Neural Network Acceptability Judgments.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Neural Network Acceptability Judgments

Reference 47

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no resolver link, observed 2026-08-15T20:31:40.332787Z

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source=arxiv_source observed=2026-08-15T20:31:40.332787Z digest=sha256:a36a4c8469eccdf77ba83284e39669f473bc5f060f702393594d435f8b89f7d7

Observation 14b7062f-c477-44bd-9547-b2ac6b8b0d12 · outbound

This paper cites Adversarial Attacks and Defenses in Images, Graphs and Text: A Review.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

Reference 48

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no resolver link, observed 2026-08-15T20:31:40.338783Z

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source=arxiv_source observed=2026-08-15T20:31:40.338783Z digest=sha256:e2c07d7b8de655fc50a3991cadd59abda6d545f04072ca3e49fd80378cf55ce8

Observation 3cefcc41-fcb7-4fdb-935d-8347c423374d · outbound

This paper cites D., Wang, F., Xiao, C., and Chen, M.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? D., Wang, F., Xiao, C., and Chen, M

Reference 49

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no resolver link, observed 2026-08-15T20:31:40.347700Z

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source=arxiv_source observed=2026-08-15T20:31:40.347700Z digest=sha256:56abb70b400b43b0de76bfe82036958da8cfb594be93352ab96c08831ae8a392

Observation edb72cab-4573-489a-81ed-1fa30f92671d · outbound

This paper cites DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 50

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source=arxiv_source observed=2026-08-15T20:31:40.357085Z digest=sha256:5f1bd43ecf4e52f5a301ec91ffe6a131e5fb42f6b1b4c2ad070bbc0591f99745

Observation 2cef1a5c-63fd-4bc6-a3e1-40074f5f0ff9 · outbound

This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 51

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source=arxiv_source observed=2026-08-15T20:31:40.367875Z digest=sha256:3e020addfaa67fde3bfec2064fed6002931eba689d51e296bdcc96b49e9ea618

Observation adf3c582-6d8d-4fe3-8400-c7290e4ba8e8 · outbound

This paper cites Backdooring instruction-tuned large language models with virtual prompt injection.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Backdooring instruction-tuned large language models with virtual prompt injection

Reference 52

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no resolver link, observed 2026-08-15T20:31:40.377615Z

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source=arxiv_source observed=2026-08-15T20:31:40.377615Z digest=sha256:1eb10ae73aa7671b2ddfb8884abf56697a376dcf6dcfc33c2c77db0abf95de25

Observation c16f0845-8c15-4bac-b618-35129e5a654f · outbound

This paper cites Rethinking stealthiness of backdoor attack against NLP models.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Rethinking stealthiness of backdoor attack against NLP models

Reference 53

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no resolver link, observed 2026-08-15T20:31:40.384137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.384137Z digest=sha256:f378eabee82e9fbbbb413a9b7b619e0903b8fa016c4af8b6274336b7adf6fe44

Observation 6094be2d-1608-43a2-ac58-7d46333bd7c7 · outbound

This paper cites LoBAM: LoRA-Based Backdoor Attack on Model Merging.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? LoBAM: LoRA-Based Backdoor Attack on Model Merging

Reference 54

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no resolver link, observed 2026-08-15T20:31:40.390930Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.390930Z digest=sha256:ac32d9e4f0c3aaabfccaf32836b8dc716691189585cad792119ef7412521af4f

Observation d292675a-275e-40f0-97a2-fd14e79e32c0 · outbound

This paper cites and Lee, K.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? and Lee, K

Reference 55

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no resolver link, observed 2026-08-15T20:31:40.399735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.399735Z digest=sha256:2f3f774ec188e7ce3b35237bb7e3bd233351b17df1c269b96451987e13aede0b

Observation f11daf17-3d75-4798-94d5-8b2cfcec5c1f · outbound

This paper cites Mer-inspector: Assessing model extraction risks from an attack-agnostic perspective.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? Mer-inspector: Assessing model extraction risks from an attack-agnostic perspective

Reference 56

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unresolved
no resolver link, observed 2026-08-15T20:31:40.405801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.405801Z digest=sha256:54ed4702f59f0a010e1e04dce946d729c248f550877b85a73e787c7225b672e7

Observation f6e0f878-30fe-41ee-b705-dfba0a580e41 · outbound

This paper cites T., Yu, M., Peng, Y., Zhang, G., and Shen, C.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? T., Yu, M., Peng, Y., Zhang, G., and Shen, C

Reference 57

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verified exact
doi, observed 2026-08-15T20:31:40.475240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.415121Z digest=sha256:f4779b385fd261b7feace18825e1cfd365ee183a888f33ed83b5949be06e6541

Observation eee6cc57-b00b-47aa-ac48-ff4f5ed705de · outbound

This paper cites H., Nadjahi, K., de Oc \' a riz Borde, H.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? H., Nadjahi, K., de Oc \' a riz Borde, H

Reference 58

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verified fuzzy
raw_fallback, observed 2026-08-15T20:31:41.472688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T20:31:40.421300Z digest=sha256:aafc18f5d3e22eb4161b85d3b88f0fdae7c20e190d393c99fd64fb4fa35c4380

Pith citing papers

Observation 798f24aa-c10e-4b7b-b7fe-936ecb403e46 · inbound

Decision Potential Surface: A Theoretical and Practical Approximation of Large Language Model Decision Boundary cites this paper.

Decision Potential Surface: A Theoretical and Practical Approximation of Large Language Model Decision Boundary Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?

Reference 12

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arxiv_id, observed 2026-05-22T13:24:53.346660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T13:22:37.107679Z digest=sha256:c2ac230a48e937e843ab6a80a4c498a4d45704541af684e659a6c32177edb73b

Observation 7d729870-d71a-4205-9e6e-e1011340541d · inbound

High-Dimensional Theory of LoRA Fine-Tuning in a Solvable Attention Model cites this paper.

High-Dimensional Theory of LoRA Fine-Tuning in a Solvable Attention Model Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?

Reference 10

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arxiv_id, observed 2026-07-02T12:16:57.385614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-28T02:14:38.644041Z digest=sha256:e314a99e89a93fbaf989994a061bc8c08902bed26285dd8643e8be389fd5cece