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Paper Citation Record · LEDGER

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection

As of 15 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2507.18202.

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

pith.paper-citation-record.v1
2507.18202 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:42:08.232124Z

measured 51 of 51 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved46
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 061e9e6b-0cfb-443c-b6f4-da90e162e514 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 1

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

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Observation 54707790-5cd3-45ca-8e16-707da5fc6080 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-06T14:42:08.004367Z digest=sha256:dd7b4d6c81c458f6a28bc847337dab64fa17b3f972234d4e35316e5233f6bf43

Observation 054197df-2196-45ff-937a-d75eef6bbae8 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 3

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source=arxiv_source observed=2026-08-06T14:42:08.009037Z digest=sha256:09fa7ad96641964a85a65443b690b7953c76ad3493252150cffeaafeacc55a4e

Observation 7edce108-614e-417a-9dbc-6a25418bc1c7 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-06T14:42:08.013831Z digest=sha256:33f4424f0e0c0f3effa14cc4f68da5723b5fd678dd01108b09bdecb681828b1f

Observation db407138-7be8-4fb4-aee6-0405f47af325 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 5

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

source=arxiv_source observed=2026-08-06T14:42:08.018398Z digest=sha256:89118eee2d3ddeeaadaf713f528ac7a1931fbef9776a19211bcbf2b333c4e6fa

Observation e47dde4e-2e6f-4036-8553-07542a4b3821 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 6

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source=arxiv_source observed=2026-08-06T14:42:08.022937Z digest=sha256:9e2f3fcec12d62df6bbbbd56c3ca898e6b588c1a3a8e7432b63ead486057e24e

Observation cfd800ae-d0f9-49bf-9411-c64e48d81520 · outbound

This paper cites The Llama 3 Herd of Models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection The Llama 3 Herd of Models

Reference 7

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source=arxiv_source observed=2026-08-06T14:42:08.027820Z digest=sha256:cd0af698072deed9b970941daeb265b3d47d5ee5dcaec3b19ca3930524bbfffc

Observation 0a8846a9-0316-4d0f-9ec2-a6103bd0786e · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-06T14:42:08.032688Z digest=sha256:3b9fdd0c8af8ed094f9731c6d771f961865ea3069d6b60ba4e23349b29b6d2d4

Observation 66966222-a3ac-4217-aa5b-1b7cb742d8c5 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 9

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source=arxiv_source observed=2026-08-06T14:42:08.036993Z digest=sha256:e47b6e1747a0b6fe24cb59eb2f75e77ada911fb24263b021f1f40282c297db7f

Observation 77917687-ce43-4167-8f44-3229fbedc9a2 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-06T14:42:08.041719Z digest=sha256:a68a7298fa5ba63e68828969771d1bca197c458cd3878790d018951b18297999

Observation 2d718f99-e4b9-49ab-a142-a7bde5391efc · outbound

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

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 11

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source=arxiv_source observed=2026-08-06T14:42:08.045898Z digest=sha256:bf72f958a2e428b6f0dbb155d1e180f771fa0b81cb2c98592c2129adf8ff9580

Observation 7fde3748-76ea-4df8-9f6b-9d913e8af87a · outbound

This paper cites Poly-encoders: Architectures and pre-training strategies for fast and accurate multi-sentence scoring.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Poly-encoders: Architectures and pre-training strategies for fast and accurate multi-sentence scoring

Reference 12

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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=2026-08-06T14:42:08.051062Z digest=sha256:df873b6b2060d03d14155083d68ee2cbc770fac3068092a06e77c77e767039ee

Observation ea8e5989-e7aa-4063-9d92-7588d51b3a77 · outbound

This paper cites Unsupervised dense information retrieval with contrastive learning.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unsupervised dense information retrieval with contrastive learning

Reference 13

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raw_fallback, observed 2026-08-06T14:42:08.968929Z

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=2026-08-06T14:42:08.055603Z digest=sha256:0b3db83a3c6c4b49e6ee6b1a4896134f90dfcacc72a551ad0e0559f8f1503ca7

Observation 538766c3-0005-4021-abf6-9d8103c1c30f · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 14

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source=arxiv_source observed=2026-08-06T14:42:08.060034Z digest=sha256:c76eef6c0fe70f2db6e3498c82b4ac68dca0dbab34cc66ee5d8f5d351d4bfa24

Observation 6b0f6a3e-767e-4a05-9808-f68ac9c019f0 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 15

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source=arxiv_source observed=2026-08-06T14:42:08.064460Z digest=sha256:c52c76e8462a5d6f4c208fb743ba30e1fdd82bc6fc2d7ad41ef33444a9e24d39

Observation eef6daa7-87db-4fef-afb0-84a5dd27c722 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 16

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source=arxiv_source observed=2026-08-06T14:42:08.068634Z digest=sha256:9d345f82db514a2a768a55fa67f093dbd0ebf1587fde08ea6a6ded049be4f2c7

Observation 23dc701e-022f-41b0-8384-f42ca8022063 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 17

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

source=arxiv_source observed=2026-08-06T14:42:08.072963Z digest=sha256:e51e309622573a6d98509082d220b00c3742a85f960098243bee9e2df8135a77

Observation cb5c1216-a79b-4cf5-bfe2-af12b31cec1f · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-08-06T14:42:08.077127Z digest=sha256:bbf784bc9b2b6912c1d369392c596f64512f7c16891705d1521e2a96b0a66126

Observation 2dab6782-910d-4ae0-b6ac-a18a7050ad6a · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 19

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source=arxiv_source observed=2026-08-06T14:42:08.081414Z digest=sha256:eba8b568f643492b21fcb0e5e47f7569b3dfa06350e214c7e19d827039b71e96

Observation 97d231cf-d76c-472c-b6a7-91df476ea2a4 · outbound

This paper cites Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov

Reference 20

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source=arxiv_source observed=2026-08-06T14:42:08.086210Z digest=sha256:ad5a6ffafcca59ce7bb6ceb681949419a6896a2929050701ca55026d47f31d64

Observation 6939cccc-c973-4c3e-892b-aac1d3f2fde5 · outbound

This paper cites u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \

Reference 21

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source=arxiv_source observed=2026-08-06T14:42:08.091545Z digest=sha256:d1711c2354cb860d8677d8bc212d99724e7ee8bd6f1c949d3f8a4d37c188398e

Observation 1334a91a-b866-4079-b675-1385fcc0e1fa · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 22

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raw_fallback, observed 2026-08-06T14:42:08.911275Z

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=2026-08-06T14:42:08.095972Z digest=sha256:d0b69ddbf0707cc458275c776d6c7dbac2ca88a22c908c09116f32dfbddc75d9

Observation 2303844d-d03d-4d4b-a1d9-22cc4a392e07 · outbound

This paper cites From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models

Reference 23

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source=arxiv_source observed=2026-08-06T14:42:08.101243Z digest=sha256:3d9a1287da32d6b154ea16d82ce3fa58634acf8675a60237fded6222ce44b866

Observation cb1fd4a6-3c8a-40e0-97b9-8cfb274af0e6 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 24

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source=arxiv_source observed=2026-08-06T14:42:08.105462Z digest=sha256:e62afe91218c5e2d6669ebdc707af85654567b6d9ab95d467eb65de20f1f558b

Observation 228a1b63-e721-4cb2-b2e8-75e0e315d1ac · outbound

This paper cites A language agent for autonomous driving.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection A language agent for autonomous driving

Reference 25

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raw_fallback, observed 2026-08-06T14:42:08.897173Z

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=2026-08-06T14:42:08.109844Z digest=sha256:66b89db35539118f19b82f697d43768bd75155167971ae0d38adf59bc72ad09b

Observation 041cde6a-f447-4859-8a24-fefa4ad1e66e · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 26

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

source=arxiv_source observed=2026-08-06T14:42:08.114256Z digest=sha256:55eb81427ed79fea433717f306578f1c1e3e6da6c8d98aef4ba24f8fc5983eb1

Observation 2eeaa05e-cff9-4d7d-8b71-592692987cb9 · outbound

This paper cites Ms marco: A human generated machine reading comprehension dataset.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Ms marco: A human generated machine reading comprehension dataset

Reference 27

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raw_fallback, observed 2026-08-06T14:42:08.866842Z

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=2026-08-06T14:42:08.118683Z digest=sha256:e50d23e04dce59d646e659893f242e572051379da50205912585c5cc00d6bb46

Observation 5f76994a-07dc-45ce-8cbc-6046fcbc5ffd · outbound

This paper cites Passage Re-ranking with BERT.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Passage Re-ranking with BERT

Reference 28

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source=arxiv_source observed=2026-08-06T14:42:08.124859Z digest=sha256:6722d25f3ecdf23fb2dd442c8519956fe600c55913a66045d232235b109c6eb9

Observation 62c2bde4-9325-4e74-bc55-a1a89baa7a02 · outbound

This paper cites Language models are unsupervised multitask learners.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Language models are unsupervised multitask learners

Reference 29

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source=arxiv_source observed=2026-08-06T14:42:08.129519Z digest=sha256:4e33a3fb484b806eeed43ac26fe9a3ea39c818002e2704511cc99a6b5ea2b8f8

Observation e640a48c-36a3-4c1b-88a4-9b2d441b8ce8 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 30

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source=arxiv_source observed=2026-08-06T14:42:08.134263Z digest=sha256:b4af8c88f435bbbd3010e0828d8f7fca005c73b9b76702ecda3aa8529a94c4b4

Observation aa0d27c1-fb5e-4325-ad2c-1e1aeef56f9d · outbound

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

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 31

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source=arxiv_source observed=2026-08-06T14:42:08.138719Z digest=sha256:aeaa32f2a2b0346e8a23f859142e18d28ec5f4e2690972dad17a7f42a1320f7e

Observation 97749d64-2648-4ea1-ab12-1a6e26bdebd3 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-06T14:42:08.834038Z

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=2026-08-06T14:42:08.143106Z digest=sha256:37eb6fd8ff2f41c2c064ad302cdd525fdadea6e4e365ecfc6fd0eb8d7ffe9de1

Observation 76208578-c0fc-4201-a6c6-03d1215f64c8 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 33

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

source=arxiv_source observed=2026-08-06T14:42:08.147327Z digest=sha256:2599b306426d8b20b5c4720039992eaf335e68aed0db6c63b0d251090b17a085

Observation 4c246378-1043-4cf7-84e6-810aa31a8b71 · outbound

This paper cites do anything now.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection do anything now

Reference 34

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source=arxiv_source observed=2026-08-06T14:42:08.151659Z digest=sha256:0122f3d69344dbd664374606572ce7d1334535895cafcd433e0f4ca1d13c472a

Observation b68f2aa6-cbb1-44b9-a29a-1a26b10a9689 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-06T14:42:08.156030Z digest=sha256:5c0a7ddc9bfa75351d1931091a0f2d4766d52c118a372d24ae188f74d72bdd40

Observation 5539a2b9-5e77-43bd-a901-86ba58ea62e9 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Gemma: Open Models Based on Gemini Research and Technology

Reference 36

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no resolver link, observed 2026-08-06T14:42:08.160712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.160712Z digest=sha256:5e2abc1b33beb9c2f26932f966ce2855bd988edb6e31137d29ef08c2592b569c

Observation 333dfac3-3e72-4197-8c66-0b0f1057b557 · outbound

This paper cites Beir: A heterogeneous benchmark for zero-shot evaluation of information retrieval models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Beir: A heterogeneous benchmark for zero-shot evaluation of information retrieval models

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-06T14:42:08.786858Z

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=2026-08-06T14:42:08.165472Z digest=sha256:395321dd45d9d0902e6cdd79f9248a6fd2099cdb5faa71c1db5bb3c207fe6b10

Observation b4649bc9-41c6-47ed-995b-8858f34936a7 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 38

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unresolved
no resolver link, observed 2026-08-06T14:42:08.170383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.170383Z digest=sha256:3f7b671188572e2c332d4a047de3ce1f0634f2343e2993b2208506f122511b2d

Observation bbdf690e-d6c9-4d9e-8b4f-02ae3b46fa3f · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 39

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unresolved
no resolver link, observed 2026-08-06T14:42:08.174851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.174851Z digest=sha256:ea0a11966c803678628a19ea72287f896ad0d4778e2d4456ad5e4ca3011231cc

Observation b0ed3078-e1cf-48e8-a0e3-949ea19c36b5 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 40

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unresolved
raw_fallback, observed 2026-08-06T14:42:08.770323Z

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=2026-08-06T14:42:08.179119Z digest=sha256:6342f4e2b605a671ea1b62f3c6fb69e1cda3cf3b3df32e6c422876636525dfbf

Observation f3398431-35f7-4cb4-8236-379b39c71325 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 41

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unresolved
raw_fallback, observed 2026-08-06T14:42:08.756307Z

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=2026-08-06T14:42:08.185025Z digest=sha256:b58d33439bf62c415768d7ffb77dfdcd6b428ddd024217b1f6d03bbc32b9d6b7

Observation da8ed986-5354-434a-80d0-a496ca3b8b19 · outbound

This paper cites BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

Reference 42

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unresolved
no resolver link, observed 2026-08-06T14:42:08.191718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.191718Z digest=sha256:a1a51991c504f1bde651c8347272e69a608b2066d801693fd093d5036db39fae

Observation 067f4f68-e03d-487f-b79d-9fedc48ca25a · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 43

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unresolved
no resolver link, observed 2026-08-06T14:42:08.196142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.196142Z digest=sha256:4a7c292c957dca062c5518c98cdaf8625641a2e184368029ce8bf248dc2afb62

Observation 6f47ebb5-822e-485d-9953-4cdd4e61fb59 · outbound

This paper cites Adversarial Decoding: Generating Readable Documents for Adversarial Objectives.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Adversarial Decoding: Generating Readable Documents for Adversarial Objectives

Reference 44

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unresolved
no resolver link, observed 2026-08-06T14:42:08.200756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.200756Z digest=sha256:167ca79375ff4b7549bd0fd1516f4f86e30a684beda8640dd0173479d35f8f2f

Observation 4af58b14-04a1-4bfc-90c7-29a326e64862 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 45

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unresolved
no resolver link, observed 2026-08-06T14:42:08.205188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.205188Z digest=sha256:e5c8dcb9b5fdeddbf2f046ecd0e88cc8378cc9898fb1bb2d1a6c264bbf36d7bd

Observation 953c2fa5-4de2-48f3-a7e2-881df1906e67 · outbound

This paper cites an unresolved cited work.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:42:08.732657Z

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=2026-08-06T14:42:08.209473Z digest=sha256:cf26980e4a5f59a8a589aa5de7372a180e6377f9c4b7d15a3d5e45b5dbf53802

Observation 7c118fca-841a-4df3-b003-6efa317bae5a · outbound

This paper cites TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation

Reference 47

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unresolved
no resolver link, observed 2026-08-06T14:42:08.213731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.213731Z digest=sha256:d470c997f2f7c9b28a43c921a56b26d09914ecf17b55938cbb28aa00e7526e8c

Observation 39d40f62-47b1-4f12-a3ce-39c1cd4c782c · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 48

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unresolved
no resolver link, observed 2026-08-06T14:42:08.218547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.218547Z digest=sha256:01b0d55821af650d0bc92ac85baec4364f8c30d17dfb01e68dd7b20bd38c7033

Observation 68edff08-d516-4b51-998d-c33ea54feda0 · outbound

This paper cites PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models

Reference 49

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unresolved
no resolver link, observed 2026-08-06T14:42:08.223022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.223022Z digest=sha256:758628550634902f57f279880f3ef9db11125688d8272c0c36a94d78fd933744

Observation e3ad181f-0b44-4d71-b7cc-ce5ca33510e4 · outbound

This paper cites online" 'onlinestring :=.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection online" 'onlinestring :=

Reference 50

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unresolved
no resolver link, observed 2026-08-06T14:42:08.227599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.227599Z digest=sha256:cd89a2923c8845c4412c0a12021ffc60bfc35db05caeb247842a6ed11b732af0

Observation 9c1c2eff-41ab-44bf-9ea0-3c7e6ecdcaed · outbound

This paper cites write newline.

Safeguarding RAG Pipelines with GMTP: A Gradient-based Masked Token Probability Method for Poisoned Document Detection write newline

Reference 51

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unresolved
no resolver link, observed 2026-08-06T14:42:08.232124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:42:08.232124Z digest=sha256:cf2abfaf8972af968b39697e35baa8453e995bdeafc358947f94ebf5ac8bc624

Pith citing papers

No inbound Pith citation observations are available.