Paper Citation Record · LEDGER

Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2405.20978.

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

pith.paper-citation-record.v1
2405.20978 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:03:45.787641Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:22:25.449430Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8745e3e3-2d20-4e63-8450-0e61d7134148 · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 105

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:33:39.199078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e7ebc5b0-46ff-41cd-81c0-70a0d67d69be · inbound

Supervising the search process produces reliable and generalizable information-seeking agents cites this paper.

Supervising the search process produces reliable and generalizable information-seeking agents Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:22:25.452473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 014879a6-c1cd-42d7-85a2-52c0aa38d537 · inbound

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models cites this paper.

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T20:03:45.787641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b246708-0df6-49dd-88e6-3ded775a622d · inbound

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level cites this paper.

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:55:54.694818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef593d0-f6d0-48a5-8f36-67f6f24d42bc · inbound

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs cites this paper.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.552925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8015dc7-d211-4107-bd14-faeb0176ae36 · inbound

Rethinking LLM Parametric Knowledge as Post-retrieval Confidence for Dynamic Retrieval and Reranking cites this paper.

Rethinking LLM Parametric Knowledge as Post-retrieval Confidence for Dynamic Retrieval and Reranking Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T23:34:28.967843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c859e909-acfb-438e-b703-b97c85e4470b · inbound

Boosting Data Utilization for Multilingual Dense Retrieval cites this paper.

Boosting Data Utilization for Multilingual Dense Retrieval Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T19:07:21.309005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5215abfb-b391-471f-ad1e-64744b79a342 · inbound

Predict the Retrieval! Test time adaptation for Retrieval Augmented Generation cites this paper.

Predict the Retrieval! Test time adaptation for Retrieval Augmented Generation Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T10:04:19.160173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ced872f-51d7-433d-88cd-b7cece6a7aa8 · inbound

Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size cites this paper.

Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:46:06.463198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5642efbc-e610-4f88-a182-d8d40aa7a406 · inbound

Mitigating Error Amplification in Fast Adversarial Training cites this paper.

Mitigating Error Amplification in Fast Adversarial Training Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:10.640287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0d99d6a4-e1f8-4bb5-b08f-d3df3a335833 · inbound

Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training cites this paper.

Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:46:34.160384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.