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Paper Citation Record · LEDGER

DMRL: Data- and Model-aware Reward Learning for Data Extraction

As of 21 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2505.06284.

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

pith.paper-citation-record.v1
2505.06284 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:39:04.641425Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

52 of 52 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved50
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1d7eeb1-b463-48fc-9c01-d22917479c94 · outbound

This paper cites online" 'onlinestring :=.

DMRL: Data- and Model-aware Reward Learning for Data Extraction online" 'onlinestring :=

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.457313Z digest=sha256:17d7a3546347bf2281fb7fb4e4d44cedd2de474208ad41784bf4ed74968814fb

Observation 4e7f6344-02ad-4cab-807f-548d5b6bd192 · outbound

This paper cites write newline.

DMRL: Data- and Model-aware Reward Learning for Data Extraction write newline

Reference 2

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source=arxiv_source observed=2026-08-15T23:39:04.461585Z digest=sha256:278367b9079b217c648ea6e60c086f9b79a4c17a8118a189af74f95bb78d211d

Observation 29e127dd-6ea0-448f-a466-f15275bc9c70 · outbound

This paper cites Yelp Dataset Challenge: Review Rating Prediction.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Yelp Dataset Challenge: Review Rating Prediction

Reference 3

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source=arxiv_source observed=2026-08-15T23:39:04.465762Z digest=sha256:bde0893736e22371dd4b53c4c0d09a0f2f8ffbcb262ad86ce16907f5591add62

Observation d88d3cb3-e4bc-464a-abcf-66dd8bb0a939 · outbound

This paper cites Qwen Technical Report.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Qwen Technical Report

Reference 4

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source=arxiv_source observed=2026-08-15T23:39:04.469796Z digest=sha256:957c74fb2703efe13bda18fc210baa1b5414e8cd28c26a6527f566880076b128

Observation 4932c4dd-7e71-404d-8cdb-e266a645fad5 · outbound

This paper cites Baichuan 2: Open Large-scale Language Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Baichuan 2: Open Large-scale Language Models

Reference 5

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source=arxiv_source observed=2026-08-15T23:39:04.473604Z digest=sha256:0a66f8a9cf69031b993521b5c44ad491c314a2b42f3fd4c29c4c1a9095eff845

Observation 50793b11-d42d-4dd6-a124-7243f9100ae6 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.477128Z digest=sha256:e643e413ba2cf10dc30ca7fcf19c17ce0e9c5a474169a6a222a26695bf0a4229

Observation 1ef7cd50-4d48-4e3d-bef8-e7327f50adba · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.480564Z digest=sha256:8d3834e6e8e0d0e64456647da8c0ccdd9cda8e1de8afc10c6a42640de7e78ce7

Observation ef7ad25e-7668-47ea-b82f-cf774fdd06b8 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.483889Z digest=sha256:6d460956e56bdca0e78d84f50f0b3a383039f7818e56be6f3a410bae4c04212e

Observation 34eed6f2-825d-4e7f-b923-04336f9b3846 · outbound

This paper cites Neural Legal Judgment Prediction in English.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Neural Legal Judgment Prediction in English

Reference 9

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:39:04.487300Z digest=sha256:bca57f7f6923f6ac1f2972286d0f054e030404f384d468809a734790ce9890f9

Observation 35f351b9-ae24-4542-8a2a-78f126e4c45c · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 11

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raw_fallback, observed 2026-08-15T23:39:05.128137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.494110Z digest=sha256:e815c897c0b801cb3132e5c174d9f673a238d594eb89c988a0fbc6965a7a6443

Observation b768bc67-380c-44e9-b288-60e2377e64f4 · outbound

This paper cites Gibberish is All You Need for Membership Inference Detection in Contrastive Language-Audio Pretraining.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Gibberish is All You Need for Membership Inference Detection in Contrastive Language-Audio Pretraining

Reference 12

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.497355Z digest=sha256:4c77c6f9018520312e8645a03353dd525d6ea3d44f6f987b93fcdb567f1de10b

Observation 034bfd2e-9c15-4bc4-a705-19dcf4e7f151 · outbound

This paper cites Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 13

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source=arxiv_source observed=2026-08-15T23:39:04.501096Z digest=sha256:ed1af97ad4d8c391c96433d90208319e45e6f43fcb50bccb830b0e3be42d9cdc

Observation 4b873466-2852-4ffe-b4f0-879ba74078d5 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.504533Z digest=sha256:4b3721c479b0465388d3852cbf02f238696c1694dc5e25c345f8e01f458c6799

Observation d3dcbfd1-b99a-44f6-afa9-d36a2907aabd · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 15

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.507504Z digest=sha256:2ec8f78d36f71527f483c78e38282c98e5c7b2b06af122ae469513a964dcdf33

Observation 232640c4-2297-45f0-af11-d329903fd17e · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

DMRL: Data- and Model-aware Reward Learning for Data Extraction ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 16

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source=arxiv_source observed=2026-08-15T23:39:04.510607Z digest=sha256:0eb37082b88cf5a7be7e25ce80f2f81127afd38317a4740cdbfd0563e95f5353

Observation 2bbdf3bb-9a31-4673-901c-443605bc29d5 · outbound

This paper cites The Llama 3 Herd of Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction The Llama 3 Herd of Models

Reference 17

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.514067Z digest=sha256:559e7e3681c2036224a6bcfcd80b990edc55ee007b48db67c626a38bf362d4d2

Observation 63394824-2a46-4a70-9655-97948711b3c3 · outbound

This paper cites Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning

Reference 18

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.517664Z digest=sha256:2726f13ada9751709e6e60f79787a2f61d3d8ddd96490356304a34513213c87f

Observation 1a73e93b-3a55-494c-a66a-5f2563fa23f1 · outbound

This paper cites Training Compute-Optimal Large Language Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Training Compute-Optimal Large Language Models

Reference 19

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.522083Z digest=sha256:89c4f7c1cbf22ad24c04c2a493e59f0c0adfda05e4429b25904eb957ac7285b5

Observation de95eea4-198e-4f93-a001-a4c26cf28bf1 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.525578Z digest=sha256:4aa0f4d76d3527473f5a4f2fa2aadd3ce3816a50dfe847675fbfa562da9789cb

Observation 6f712e05-036e-4e1d-a116-a46589878d2c · outbound

This paper cites Training Data Leakage Analysis in Language Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Training Data Leakage Analysis in Language Models

Reference 21

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.528843Z digest=sha256:4f940ec04bef8891645fc66ff46b4d42ebd1898c873e1aebf82b71804f74f58d

Observation 8f45686f-7a91-44f8-a0b6-6f73bbd1e5ca · outbound

This paper cites Measuring Forgetting of Memorized Training Examples.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Measuring Forgetting of Memorized Training Examples

Reference 22

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source=arxiv_source observed=2026-08-15T23:39:04.533270Z digest=sha256:ecc80d77246ce4deeb6aea4ed6e66def452cfd9af52c9ad5713e7609810e3d10

Observation d7099288-ef38-4037-8fc1-ffd689207ac4 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.537285Z digest=sha256:d2ee525ff5102487d26c61022d678cf34042c4f4fae8f3ee92cd856e8eff68ce

Observation c56af638-3299-40fd-80de-656b4f89dca3 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.540249Z digest=sha256:e86a9ab4802db31e1287fd8925b8dceb277db3f2f011628b416ce33f02e02304

Observation 2b603f1e-ed03-41fe-aa9e-cd52bf9a0bd3 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-15T23:39:04.543291Z digest=sha256:7e7aad241e25abf378eacab494ca7185ae92e0de2fd5d296ad0353656e644ac4

Observation 206378ca-cd9d-4f03-9d93-fb6493062bdd · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 26

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source=arxiv_source observed=2026-08-15T23:39:04.546265Z digest=sha256:9669ed05af4c3f0a373847bd1b92834c9d1410290c5f87d4cb6417b5605346bf

Observation 32592992-01cb-4497-a287-6d56e90f44a0 · outbound

This paper cites Models of human preference for learning reward functions.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Models of human preference for learning reward functions

Reference 27

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source=arxiv_source observed=2026-08-15T23:39:04.549420Z digest=sha256:6aa68c35a6c6fb44ef0f035443ff21f63bbfaace343dbe267d8308b44731a9e4

Observation 0e70d11f-103d-4448-ac26-2bf7cf4802e8 · outbound

This paper cites Does BERT Pretrained on Clinical Notes Reveal Sensitive Data?.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Does BERT Pretrained on Clinical Notes Reveal Sensitive Data?

Reference 28

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source=arxiv_source observed=2026-08-15T23:39:04.552704Z digest=sha256:ef78a871f1e45abc0bf78b84bb9c7f0e047dfe3b8cbca7e227383b2b25f86a49

Observation 06eb2465-f36d-4ff4-89aa-66242f99055d · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-15T23:39:05.072149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.555888Z digest=sha256:c11a20dfd7a97765c43ab2c5e91a61674f3734638c1bef6799412304e0bdeecf

Observation 4d62aedb-c229-472f-97f1-672273eb6c61 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 30

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raw_fallback, observed 2026-08-15T23:39:05.062072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.558899Z digest=sha256:1779d51ce3cc7400e289f571f2503c24ec1ee3203d0f419d67aa5d53bc1a675f

Observation 9665581d-ecd3-450f-943f-53670a5a7ea8 · outbound

This paper cites TUNI: A Textual Unimodal Detector for Identity Inference in CLIP Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction TUNI: A Textual Unimodal Detector for Identity Inference in CLIP Models

Reference 31

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verified exact
local_arxiv, observed 2026-08-15T23:39:04.768336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.561946Z digest=sha256:c317848c43614069385b811146ea016fbcc08be85acc1f4cd70366595176b100

Observation 5dbc892d-a385-4f60-a3d4-176ca4a7344b · outbound

This paper cites note bloat.

DMRL: Data- and Model-aware Reward Learning for Data Extraction note bloat

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-15T23:39:05.051949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.565309Z digest=sha256:be61769cca8dfbd22b9c175e0f0cb493450ec3a579bcb441e1daad1123e83187

Observation 519ad9db-0f9d-4aea-a96e-b5d503063391 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.568305Z digest=sha256:83a3291bb2a4ccb23e965d3210afbf780168a0bff281cf128108aac5cd57f713

Observation bbdce563-d3dd-4b5d-bdff-9d1455f41857 · outbound

This paper cites Scalable Extraction of Training Data from (Production) Language Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Scalable Extraction of Training Data from (Production) Language Models

Reference 34

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source=arxiv_source observed=2026-08-15T23:39:04.571444Z digest=sha256:2e6052f6b2979235c9b71eb999964df1704638c430daa8219fb08951e2535783

Observation 2a4d3b75-120b-41a8-bd8d-f688c5ee8e4e · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 35

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raw_fallback, observed 2026-08-15T23:39:05.036278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.575094Z digest=sha256:b0aa3a73f97eaa35eec2f3674964868cffab166a3582f4e536aceda74578425a

Observation 9c18248a-c9b9-43c6-8403-269d70772a45 · outbound

This paper cites LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage.

DMRL: Data- and Model-aware Reward Learning for Data Extraction LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.578072Z digest=sha256:d679cf870a945d7a4ff49bc5d70fd76eb548a21e26f0dcab6e0fd6325f6c20f3

Observation cd7861f2-49a3-4ecc-93f4-aa614d15a2fa · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 37

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source=arxiv_source observed=2026-08-15T23:39:04.581556Z digest=sha256:0e7f63335217c7cff00490c9fba515826cab03588fe5b3351dd3861af16a5321

Observation 944a99ab-8976-4dc0-b89f-61bbc2178f63 · outbound

This paper cites SelfPrompt: Autonomously Evaluating LLM Robustness via Domain-Constrained Knowledge Guidelines and Refined Adversarial Prompts.

DMRL: Data- and Model-aware Reward Learning for Data Extraction SelfPrompt: Autonomously Evaluating LLM Robustness via Domain-Constrained Knowledge Guidelines and Refined Adversarial Prompts

Reference 38

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.589952Z digest=sha256:89ed9a434edd0a7a2fcbda48fc8f11f38192e9bb0eb77cd1adbe4c43f2ba5ded

Observation 5d1af099-603a-4257-8fbc-1b813e669d0b · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 39

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.594330Z digest=sha256:5916aced56436443f90456f662e9d1e15ede9d1438a3a6db90e3114fe0cf818d

Observation 2adee9b4-b7e3-4521-a674-f34024fb777a · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 40

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no resolver link, observed 2026-08-15T23:39:04.597532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c9481b93-da40-4f44-852f-f17a2ef9f004 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 41

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no resolver link, observed 2026-08-15T23:39:04.600881Z

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Observation 11374d0e-88e1-4338-a95f-61be6617e568 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 42

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unresolved
raw_fallback, observed 2026-08-15T23:39:05.001079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation e03fc48e-bba8-4f5a-b8f5-5ef2716f2aa4 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Neural Machine Translation of Rare Words with Subword Units

Reference 43

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no resolver link, observed 2026-08-15T23:39:04.607490Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:39:04.607490Z digest=sha256:5677bd6f2123aad551f844ef695f2e0872aac308281562690175b6c10d275e7e

Observation 7c897ac8-3555-44c3-b84f-c057702da972 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 44

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no resolver link, observed 2026-08-15T23:39:04.611030Z

Source-reported events for the cited work

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Observation da9d2a0a-bed2-4e99-a730-9f7e5de6e995 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 45

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no resolver link, observed 2026-08-15T23:39:04.614370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.614370Z digest=sha256:8977eb2243061bb90fbdbfc01cde4aafd78e8abf6d077df8529a1905c80c81c4

Observation b19bc193-932d-4eb5-8407-f99fd1bd8ab1 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 46

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no resolver link, observed 2026-08-15T23:39:04.617630Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:39:04.617630Z digest=sha256:00a1a34bd0e985c408deb5ffce3105e385b802830189131cb5488c2b7bb6dfa3

Observation 074983fb-27c1-496c-8869-2a8d55bc88dd · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 47

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unresolved
raw_fallback, observed 2026-08-15T23:39:04.985070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.621043Z digest=sha256:57d40df28860ea7bf23915255b9951cde607f2ba9a7939986659ce0f585e1a06

Observation 9008bd6f-6915-482c-8bec-acf8ee915d9a · outbound

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

DMRL: Data- and Model-aware Reward Learning for Data Extraction Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 48

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no resolver link, observed 2026-08-15T23:39:04.624178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.624178Z digest=sha256:f26fa89e710ae0ec92728a464cea07457933d1e62c00c8d4ae2be4f60e451bd9

Observation c73e3805-2381-4811-9ad3-1c1406b5dd60 · outbound

This paper cites Differentially Private Fine-tuning of Language Models.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Differentially Private Fine-tuning of Language Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T23:39:04.627594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:39:04.627594Z digest=sha256:1c534a814d0f8ee97352495a3d2713ce70b456b9ba19ad0463b1b4c94afd4560

Observation 36a57df2-7c08-49db-96cb-4718ccc7ad37 · outbound

This paper cites Assessing Prompt Injection Risks in 200+ Custom GPTs.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Assessing Prompt Injection Risks in 200+ Custom GPTs

Reference 50

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unresolved
no resolver link, observed 2026-08-15T23:39:04.631255Z

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source=arxiv_source observed=2026-08-15T23:39:04.631255Z digest=sha256:a37b441c9321554f48dbd0453429669f7d0265e7bf92bd3f34faa50802305bba

Observation 94687acb-66e8-4171-bed0-1544a715a9f0 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 51

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unresolved
raw_fallback, observed 2026-08-15T23:39:04.974969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.634916Z digest=sha256:72e8e84434574d55f534756b3a75bc0d993e85662b88e3307451783fcb2ae5dc

Observation 2d982d1a-a949-4b68-afce-71f9f0510975 · outbound

This paper cites an unresolved cited work.

DMRL: Data- and Model-aware Reward Learning for Data Extraction Unresolved cited work

Reference 52

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unresolved
raw_fallback, observed 2026-08-15T23:39:04.965018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T23:39:04.638270Z digest=sha256:cac867e875b0ff5e56774c792c259b2580f6695ff36d088d4d01435a13065001

Observation f956bd2d-24cd-455b-99d4-92ce6b352209 · outbound

This paper cites From Demonstrations to Rewards: Alignment Without Explicit Human Preferences.

DMRL: Data- and Model-aware Reward Learning for Data Extraction From Demonstrations to Rewards: Alignment Without Explicit Human Preferences

Reference 53

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source=arxiv_source observed=2026-08-15T23:39:04.641425Z digest=sha256:8633a5c743e97ee391b27fefaeecde01a400c0cc8818f9c405d1f2499d21fadd

Pith citing papers

No inbound Pith citation observations are available.