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Paper Citation Record · LEDGER

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 4 inbound Pith citation observations for arXiv:2506.11415.

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

pith.paper-citation-record.v1
2506.11415 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:15:40.046988Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T19:27:04.088604Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T02:07:33.487385Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact2
  • verified fuzzy17
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34b8da34-5773-4633-9537-ff6ef61a32a1 · outbound

This paper cites Harnessing the power of llms in practice: A survey on chatgpt and beyond,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Harnessing the power of llms in practice: A survey on chatgpt and beyond,

Reference 1

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no resolver link, observed 2026-08-07T04:15:35.566973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:35.566973Z digest=sha256:74569139f625df4b46f67fada8e2d17d821267e48d8e35ed59d38c174c47d202

Observation b2a3dc78-fc46-4051-a84c-dab78e38f203 · outbound

This paper cites The frontier of data erasure: A survey on machine unlearning for large language models,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs The frontier of data erasure: A survey on machine unlearning for large language models,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.848229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:35.616062Z digest=sha256:880ff755be7c3f82623b6c6ff042af330f5c27a785f474c06080bbd4acfcb18d

Observation b09ba661-2336-48a2-b27d-6c750a001dca · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 3

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no resolver link, observed 2026-08-07T04:15:35.690543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:35.690543Z digest=sha256:c7a046e98725f2c8cbe5eea03fa44b3e78c6a49827c4aad0319671a4075168d7

Observation 1432189a-e0ea-466b-9550-a77f3b42c579 · outbound

This paper cites SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model

Reference 4

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unresolved
no resolver link, observed 2026-08-07T04:15:35.772041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:35.772041Z digest=sha256:b08855e0659cc5fc1d1c795eae9074f0d7ed351aadee90be06b974404fe33e8a

Observation daf20d88-fa05-4d3b-a8a3-06ff188b4a43 · outbound

This paper cites When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?

Reference 5

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no resolver link, observed 2026-08-07T04:15:35.857559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:35.857559Z digest=sha256:220f0321e85b1b8579102ead928317bde3dc9afc0b04d2992b59dc738c45263c

Observation 75a9ab1a-5f1c-4ae6-a186-69a611c7ae31 · outbound

This paper cites Poison-RAG: Adversarial Data Poisoning Attacks on Retrieval-Augmented Generation in Recommender Systems.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Poison-RAG: Adversarial Data Poisoning Attacks on Retrieval-Augmented Generation in Recommender Systems

Reference 6

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local_arxiv, observed 2026-08-07T04:15:40.648085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:35.912449Z digest=sha256:36b0ede3054acfc7376a22b74c6f2188e7e74b7724a34f2cb3cfa3525ce498de

Observation 187d8aaa-509a-4ab2-a7de-a92141cd0eb0 · outbound

This paper cites Poisoning Retrieval Corpora by Injecting Adversarial Passages.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Poisoning Retrieval Corpora by Injecting Adversarial Passages

Reference 7

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no resolver link, observed 2026-08-07T04:15:36.006831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:36.006831Z digest=sha256:e2f1a0e8bd459be8ec719a82d26a75d1e4c18a8fb829c390a1592d0a9eadfaf6

Observation 13a82056-0b6d-4466-a75e-dd3ca5f81099 · outbound

This paper cites Bias unveiled: Investigating social bias in llm-generated code,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Bias unveiled: Investigating social bias in llm-generated code,

Reference 8

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raw_fallback, observed 2026-08-07T04:15:41.835287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:36.072263Z digest=sha256:633cd34d981ee913b5a37c63e081330581f44d79a6e85d1c9ade573dd674984b

Observation 8eaf4be9-7f05-4ded-a15a-17ea84056a0c · outbound

This paper cites Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception

Reference 9

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:15:36.203287Z digest=sha256:f74423870db0ea6b6bbb411fb2d56fbb97a2d5b782bc77660811d2261112095b

Observation 3ec645ee-b390-4fae-ae3b-c8c14b95b356 · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 10

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source=pdf_text observed=2026-08-07T04:15:36.355589Z digest=sha256:8175f7d9334ac6a307e0a41144df575b5d879c7ddbb6efbffe0622c56a657cb5

Observation 6f33f15e-0820-44cb-8058-050ad547d44d · outbound

This paper cites Evaluating interfaced llm bias,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Evaluating interfaced llm bias,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.826985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:36.535740Z digest=sha256:7872500561b6ab03515cfc1dd1ed801a92a5ac6f84e98ba0e7a6825df9542360

Observation fe62d919-66d7-4147-95b8-bca1de9ad3d2 · outbound

This paper cites Do fairness interventions come at the cost of privacy: Evaluations for binary classifiers,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Do fairness interventions come at the cost of privacy: Evaluations for binary classifiers,

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.819380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:36.698727Z digest=sha256:c0d8ee3fcc0c3961f24b87d86b6aafbacbd7f48ec2755bf3216ff8d1d8071e2f

Observation d439efad-5b11-4f99-86ba-958d087b3246 · outbound

This paper cites Afed: Algorithmic fair fed- erated learning,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Afed: Algorithmic fair fed- erated learning,

Reference 13

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raw_fallback, observed 2026-08-07T04:15:41.811596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:36.850442Z digest=sha256:47ffb9f468b62ff5983e4f6665f5be4848fc1b9bc07976399b03f7e7eea65d4e

Observation adef5cc5-6154-4189-9bcd-3313fcc0f184 · outbound

This paper cites Bias and unfairness in information retrieval systems: New challenges in the llm era,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Bias and unfairness in information retrieval systems: New challenges in the llm era,

Reference 14

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source=pdf_text observed=2026-08-07T04:15:36.982457Z digest=sha256:fdc0567adf509a935c78d1da45dad2511668b2cf284585e9b654d8f57a261b2f

Observation af747507-28dc-470f-b357-80975765f165 · outbound

This paper cites Fine-tuning a biased model for improving fairness,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Fine-tuning a biased model for improving fairness,

Reference 15

Resolution
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raw_fallback, observed 2026-08-07T04:15:41.799170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:37.150598Z digest=sha256:d073344078e69201a2a92022e51632b7c01098f1bb1cac1666d13cff5eeed709

Observation 8fc35f26-8be6-4fea-adff-a3631b43842c · outbound

This paper cites Distilling fair representations from fair teachers,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Distilling fair representations from fair teachers,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.791324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:37.328868Z digest=sha256:64e9708e1bc8c2ad73afa3b0b571c9bec407970598cdac7d3cd9ff7181921f74

Observation 9f372f77-b04b-45e4-91f1-2f7b1bf06bab · outbound

This paper cites Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation Systems.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation Systems

Reference 17

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:15:37.430708Z digest=sha256:ad81a6ad857518005f39dcf641c8ca9beae26de5d2b3146140f8ec2ae37b64f2

Observation 909fedb8-9465-45fc-beb1-98cd369b2a73 · outbound

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

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation

Reference 18

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source=pdf_text observed=2026-08-07T04:15:37.510858Z digest=sha256:154b6d93b44bef9cf3f422d163dc62a33f82f02832e7c135d563cfebf7aeed35

Observation f584e68d-30a1-4156-b7b2-43865f35950b · outbound

This paper cites A survey on machine unlearning: Techniques and new emerged privacy risks,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs A survey on machine unlearning: Techniques and new emerged privacy risks,

Reference 19

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raw_fallback, observed 2026-08-07T04:15:41.782834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:37.599065Z digest=sha256:66012ec1ed737d091e20b204e156ed0ed56de0b6eb17d126a8f89f06fb10edb7

Observation 5afa17ca-c945-4a39-ba28-e986a063f3c4 · outbound

This paper cites Certifiably robust rag against retrieval corruption,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Certifiably robust rag against retrieval corruption,

Reference 20

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source=pdf_text observed=2026-08-07T04:15:37.692270Z digest=sha256:ff3db3c63cb9ec9285e0754113bd74cce8bcca0df3f9a49f3493312766715855

Observation 92521ab5-c6cd-4af9-ae5b-8f788b9b30fa · outbound

This paper cites Average and strict gan-based reconstruction for adversarial example detection,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Average and strict gan-based reconstruction for adversarial example detection,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.773788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:37.803400Z digest=sha256:abc664bde2c20071987b6d14dc973aeae16ac925b1f6b06009a966c31f6d3a62

Observation cfd79da1-2312-458f-aaf2-515ba5a2998b · outbound

This paper cites Generative adversarial JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 17 networks unlearning,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Generative adversarial JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2021 17 networks unlearning,

Reference 22

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raw_fallback, observed 2026-08-07T04:15:41.765262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:37.925661Z digest=sha256:e3039c69e83ef70ccfaf575c898b33e36ab5b0790a2cf23b081b17c45e633fa0

Observation 69e8a5cf-3992-4724-a474-43a684cf879e · outbound

This paper cites Bibliometric analysis of educational research in 2017 to 2021 using vosviewer: Google scholar indexed research,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Bibliometric analysis of educational research in 2017 to 2021 using vosviewer: Google scholar indexed research,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:38.045564Z digest=sha256:0d5897ddc81219dea8847f34d0c6fa2d5a16d56fe1684aeec7765d564f560839

Observation cf8e60e1-54e6-4f11-a34a-60288ebb8cf1 · outbound

This paper cites Overview of trec 2021.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Overview of trec 2021

Reference 24

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raw_fallback, observed 2026-08-07T04:15:41.745013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:38.163073Z digest=sha256:56bf8e0979eb6db94a35dfce8b8c0a5a62c027a5145a382da2538c66ec2190c0

Observation 73cfcd32-232b-4344-ae64-d5592c5456ea · outbound

This paper cites Bias and fairness in large language models: A survey,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Bias and fairness in large language models: A survey,

Reference 25

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no resolver link, observed 2026-08-07T04:15:38.318096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:38.318096Z digest=sha256:61a5cb9d55953d9d0fc1f72e40abecfdcfe7941e7f06a9bc75f2d78d084256d0

Observation 45498480-73f5-4c1b-ac98-a4ba784bcf61 · outbound

This paper cites An empirical study of rich subgroup fairness for machine learning,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs An empirical study of rich subgroup fairness for machine learning,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.727321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:38.480332Z digest=sha256:33c405abb6939b0b4869275b7d0b1dc87823a65423d094ee6489613e3e1dc52c

Observation 82388f54-24fe-4643-a53f-1f130811e93d · outbound

This paper cites Fair prediction with disparate impact: A study of bias in recidivism prediction instruments,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Fair prediction with disparate impact: A study of bias in recidivism prediction instruments,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:38.567555Z digest=sha256:b654c1d60b1a27df5afb853fd5ffbf4a9f36b7290997bb09c90eca93544a0ce3

Observation 87cd06f6-aba5-4fe0-b5ad-df99a0cf46c5 · outbound

This paper cites Certifying and removing disparate impact,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Certifying and removing disparate impact,

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:38.635214Z digest=sha256:8516b2ac02951835a155e08860b9fb1f808a90fc023146ab7fcfdec6565a3d80

Observation 573329f7-b5db-4245-84ef-0fa19187c5be · outbound

This paper cites TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models

Reference 29

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source=pdf_text observed=2026-08-07T04:15:38.715186Z digest=sha256:70af07bc4ab8121e5f43acd14621c39273b76b91ff9e7a0560308e45a83d96e7

Observation 658ee460-5d59-4cf6-96ba-1e980303fe72 · outbound

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

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

Reference 30

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no resolver link, observed 2026-08-07T04:15:38.811538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:38.811538Z digest=sha256:1ca794aa521d53c9f687295e6f3d5a4bd282d72f20cfd9835fa6d94d3dd67e88

Observation c8111ef8-2935-4542-afef-9c37f54c55f8 · outbound

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

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:38.906102Z digest=sha256:e65b1ce1ce65ed8e315a388865c6daa6df5cacbd55d27a75c2e32dc5d4336c7b

Observation e36aa399-4b1a-4577-8e6e-33a9cf155af4 · outbound

This paper cites Pandora: Jailbreak GPTs by Retrieval Augmented Generation Poisoning.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Pandora: Jailbreak GPTs by Retrieval Augmented Generation Poisoning

Reference 32

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no resolver link, observed 2026-08-07T04:15:38.974260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:38.974260Z digest=sha256:9faa8c78f88e23978dd77434ff9dc0aa7ef8790185f4cad80d042ced33938726

Observation dcdc88b1-7970-45a5-be4f-8d5f9bbdb142 · outbound

This paper cites No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users

Reference 33

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no resolver link, observed 2026-08-07T04:15:39.055744Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T04:15:39.055744Z digest=sha256:7caf9539df51da9c61d7c61929b658fd298b66c199c51457bc2339f79531d466

Observation 9f9d40ef-403d-499a-b2be-0d7ebff12570 · outbound

This paper cites Towards fair rag: On the impact of fair ranking in retrieval-augmented generation,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Towards fair rag: On the impact of fair ranking in retrieval-augmented generation,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.702706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:39.122130Z digest=sha256:ca32d18bf637f6c7c7d35b7f6ed5e67032f9bcdb8ab2ba47b51a54b3761327fa

Observation 1ef45207-4509-4fed-b7a3-445ac6a03d86 · outbound

This paper cites Fairrag: Fair human generation via fair retrieval augmentation,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Fairrag: Fair human generation via fair retrieval augmentation,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.641751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:39.188166Z digest=sha256:d11bb88f44911385dad91a5de4fb8509e6a6ac5762d4f4d99ba7e7bd7ee0141d

Observation a99450ee-373e-4c87-b658-ea002937522c · outbound

This paper cites Mitigating Bias in RAG: Controlling the Embedder.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Mitigating Bias in RAG: Controlling the Embedder

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:15:40.277826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:39.255881Z digest=sha256:4e1404568e2135c81ed46636f21f70bb4078f7ed8c1eb0d049285175e1615c6f

Observation 5d2c6711-89b0-4c87-8668-d7682c2d1e5b · outbound

This paper cites Queen: Query unlearning against model extraction,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Queen: Query unlearning against model extraction,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:15:41.432744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:39.326283Z digest=sha256:6bf26a6e4e7d74a1063ad1a929994a06aa0d0ca946ca090af703479b84609c0d

Observation 84f2a46e-05ac-479e-bc8b-3fa74943fcad · outbound

This paper cites an unresolved cited work.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-07T04:15:41.161738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:39.393919Z digest=sha256:8c48aa14f89e8b097f30ebb1d1f9b3b91d4b18e19d31b6c81fc29b21aaa64a8f

Observation 13595b9b-a24f-44ab-b7ea-b88e44bf2bfb · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:39.511060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:39.511060Z digest=sha256:1103288a1681fa82056894a84db12b2695ebf3eb4f1d22bbc11198d13c3a9c3a

Observation 0f79b251-ca69-4da2-a941-8a81d40c994e · outbound

This paper cites Qwen2.5 Technical Report.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Qwen2.5 Technical Report

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:39.571907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:39.571907Z digest=sha256:839c2fb74e26d82a791a263a099f863dfe402865c4aea170a29866311ea32c16

Observation c6ac0879-a7e0-4dff-b724-2f3a27484495 · outbound

This paper cites The Llama 3 Herd of Models.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs The Llama 3 Herd of Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:39.695587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:39.695587Z digest=sha256:79e82b302effce6718e7072abe48315e6c82368ff6333c5d71fe56a28f62bf9d

Observation 1277735d-a8f0-4a21-aab2-20c7aaa0e98b · outbound

This paper cites BBQ: A Hand-Built Bias Benchmark for Question Answering.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs BBQ: A Hand-Built Bias Benchmark for Question Answering

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:39.789180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:39.789180Z digest=sha256:30fa173d9ea9159a2a02ab0e498a7733c383d28cad8d9945d33ec2c046474de3

Observation 6f6f5e77-d15e-49f3-807f-3f4d8d8d3355 · outbound

This paper cites StereoSet: Measuring stereotypical bias in pretrained language models.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs StereoSet: Measuring stereotypical bias in pretrained language models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:39.884508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:39.884508Z digest=sha256:e8ded701ab6d3c9a791b2a0989090145a78d6318e0a3c2263a2f97bf4cb9c68c

Observation ee9759e2-85c1-427b-ab09-7da2a1cf21bf · outbound

This paper cites Pyserini: A python toolkit for reproducible information retrieval re- search with sparse and dense representations,.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Pyserini: A python toolkit for reproducible information retrieval re- search with sparse and dense representations,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:15:40.854849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:15:39.978557Z digest=sha256:6d42cb62fdd3d338a945b758a035d73858b0728f7927051ed435c91f0a8e3c23

Observation 77506a78-4796-4cbc-94fe-84a85cf2d5a9 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T04:15:40.046988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:15:40.046988Z digest=sha256:45481579b4c108ddfe52e4589c70e8c68ff72321c082265c5d8321f24c19b044

Pith citing papers

Observation 5164d2d3-79ba-4a74-a880-8b9bbf275098 · inbound

Epistemic Bias Injection: Manipulating LLM Opinion via Selective Context Retrieval cites this paper.

Epistemic Bias Injection: Manipulating LLM Opinion via Selective Context Retrieval Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T19:27:04.088604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:27:04.088604Z digest=sha256:77ebc97f5bd50b2b1a2f342380addb78968cbc4e4f38a57aaa41c161365f8564

Observation 425209cb-a80f-49e6-bc06-4261471c5c19 · inbound

Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions cites this paper.

Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:21:03.653846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:00:05.173476Z digest=sha256:3563d76dbe299f0f77ef4a801e619216553f5a9f24296179dbc7498b9aa96835

Observation ae227b23-faea-48a1-abfe-a839cf5a023b · inbound

SoK: Colluding Adversaries in Machine Learning Pipelines cites this paper.

SoK: Colluding Adversaries in Machine Learning Pipelines Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs

Reference 104

Resolution
verified exact
arxiv_id, observed 2026-07-03T02:07:33.489406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T16:10:51.471822Z digest=sha256:923b0262cb005774623e8a41840c036643f7621b44cce871f2d182d1f88bfcd8

Observation e29d505d-0a96-438a-bed2-6fe1a025f584 · inbound

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability cites this paper.

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs

Reference 195

Resolution
unresolved
no resolver link, observed 2026-07-14T12:01:22.824663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T12:01:22.824663Z digest=sha256:f90b647f96babded227bd363d85940fd18bf63b30e88143f8173fd8ff4e013fb