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Paper Citation Record · LEDGER

Contrastive Weak-to-strong Generalization

As of 15 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2510.07884.

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

pith.paper-citation-record.v1
2510.07884 v3

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:56:40.844714Z

measured 49 of 49 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

49 of 49 outbound references displayed

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  • verified fuzzy0
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0d32023-c3bd-447e-b6cb-ae06513c6815 · outbound

This paper cites MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.

Contrastive Weak-to-strong Generalization MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

Reference 1

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source=arxiv_source observed=2026-08-04T10:56:35.942089Z digest=sha256:6b42571e9911d1be8ef5b7d9781f52631a3178d77d750267781a7ae2f014d9df

Observation 137215f9-6c5f-4dd6-a1d9-150e46164c14 · outbound

This paper cites A General Language Assistant as a Laboratory for Alignment.

Contrastive Weak-to-strong Generalization A General Language Assistant as a Laboratory for Alignment

Reference 2

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source=arxiv_source observed=2026-08-04T10:56:36.020206Z digest=sha256:c6dab208fb2fe66180027ef0c218f30f09d0939173534a529b2daf7ceb2284e9

Observation ebc5bec7-4de1-4165-ade1-213b495b916e · outbound

This paper cites Rank analysis of incomplete block designs: I.

Contrastive Weak-to-strong Generalization Rank analysis of incomplete block designs: I

Reference 3

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source=arxiv_source observed=2026-08-04T10:56:36.075904Z digest=sha256:b2d468ae933468d3d44b70de842f95e3a307830f9f16dc82f244ffe16655c080

Observation 8f65b2e0-0934-4947-85f0-8d4be91fb90c · outbound

This paper cites Weak-to-strong generalization: Eliciting strong capabilities with weak supervision.

Contrastive Weak-to-strong Generalization Weak-to-strong generalization: Eliciting strong capabilities with weak supervision

Reference 4

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source=arxiv_source observed=2026-08-04T10:56:36.155865Z digest=sha256:2d5bff6baf5ea03abff7fc116ed550b3d0087e67d3c217b9ce7050bb27666ba7

Observation c2108adf-6aec-41b6-a562-6136b1153a19 · outbound

This paper cites Christiano, Jan Leike, Tom B.

Contrastive Weak-to-strong Generalization Christiano, Jan Leike, Tom B

Reference 5

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source=arxiv_source observed=2026-08-04T10:56:36.216263Z digest=sha256:9c3a5af95316306d2f413c065c6bc5ece5a72bde5977aade5fdf1f580a2288f5

Observation 222f5780-28ae-4f2b-ad85-aa77019220b4 · outbound

This paper cites Glass, and Pengcheng He.

Contrastive Weak-to-strong Generalization Glass, and Pengcheng He

Reference 6

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source=arxiv_source observed=2026-08-04T10:56:36.298997Z digest=sha256:f2a2bbdb61b6793fdf84516cfae748adbe0460289483e0da9b55b6ea85df7b1f

Observation 5b06728d-ddae-4809-b09c-001d18937a55 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Contrastive Weak-to-strong Generalization Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

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source=arxiv_source observed=2026-08-04T10:56:36.352868Z digest=sha256:a6bcd57329f8e79378a198802ad0f911f9da9ac92c531c9cbd8d59515656a4dc

Observation 64d66d1d-f8e5-4522-b728-7f24d2c4f2df · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Contrastive Weak-to-strong Generalization Training Verifiers to Solve Math Word Problems

Reference 8

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source=arxiv_source observed=2026-08-04T10:56:36.416809Z digest=sha256:a3a1a7102eb05fd0a7a8a09366c7d8a6c46238752e2fc75e984edd6d4ae14f8a

Observation 25faaa4e-54c0-4856-aef4-dd609874f25c · outbound

This paper cites ULTRAFEEDBACK: boosting language models with scaled AI feedback.

Contrastive Weak-to-strong Generalization ULTRAFEEDBACK: boosting language models with scaled AI feedback

Reference 9

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source=arxiv_source observed=2026-08-04T10:56:36.460106Z digest=sha256:bf639d8f358ad4481a426b5da9acec36d77f6add19109a66001892be120dc389

Observation 464efe5a-f56b-4253-b89d-bceb7ca8be1b · outbound

This paper cites Process Reinforcement through Implicit Rewards.

Contrastive Weak-to-strong Generalization Process Reinforcement through Implicit Rewards

Reference 10

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source=arxiv_source observed=2026-08-04T10:56:36.521543Z digest=sha256:71839b9f89e7dbb28747fdb641a8cdf9d1ebe2776f24ac4a863878999da3e1a4

Observation c90f6ead-2433-4d9e-a3c8-a4cba3a8a934 · outbound

This paper cites The Llama 3 Herd of Models.

Contrastive Weak-to-strong Generalization The Llama 3 Herd of Models

Reference 11

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source=arxiv_source observed=2026-08-04T10:56:36.565292Z digest=sha256:a370719150accc1ab9e5fcaba0c62fd582fe2b7737b1d4fae0d8b25f0f23abe9

Observation 1eda65ab-faf1-49d5-94c6-c370c8350817 · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Contrastive Weak-to-strong Generalization Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 12

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source=arxiv_source observed=2026-08-04T10:56:36.656752Z digest=sha256:98e1ccc98aa23aa67d7bd0afedbb7e3002109a009fad77875f1860d1d8dd54fd

Observation e38380c1-e2d8-433c-87a3-0735dac66086 · outbound

This paper cites Artificial general intelligence: Concept, state of the art, and future prospects.

Contrastive Weak-to-strong Generalization Artificial general intelligence: Concept, state of the art, and future prospects

Reference 13

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source=arxiv_source observed=2026-08-04T10:56:36.699319Z digest=sha256:618a2d5c099208d7dbfa28aace8fb52c9f442c48b79d479bb7080792bed9ea63

Observation 2d0f0978-c980-4d6a-96c5-3878d02baace · outbound

This paper cites Measuring massive multitask language understanding.

Contrastive Weak-to-strong Generalization Measuring massive multitask language understanding

Reference 14

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source=arxiv_source observed=2026-08-04T10:56:36.761532Z digest=sha256:cd68065b25d67a336107004ed097781de22adf28db133a7305ad2f12246073bc

Observation 70c9cd82-666c-4b46-baa6-cf060e9a7184 · outbound

This paper cites ORPO: monolithic preference optimization without reference model.

Contrastive Weak-to-strong Generalization ORPO: monolithic preference optimization without reference model

Reference 15

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source=arxiv_source observed=2026-08-04T10:56:36.815932Z digest=sha256:7c75368f0783b22220d9b595e44140cae69428b08ff603fae8add7d89b215cfa

Observation f3aebe1a-a527-4b0c-b02f-e70e20b6a78b · outbound

This paper cites AI Alignment: A Comprehensive Survey.

Contrastive Weak-to-strong Generalization AI Alignment: A Comprehensive Survey

Reference 16

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source=arxiv_source observed=2026-08-04T10:56:36.895128Z digest=sha256:89989b4e6556c76e690f6abf89f1cb06e47ef44bd6113732a2a045b2864ee8ac

Observation 6779d713-240a-4602-8131-0018306eae3e · outbound

This paper cites The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment.

Contrastive Weak-to-strong Generalization The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment

Reference 17

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Observation 5ef137cd-12a6-4ccc-8984-dd172af87b0c · outbound

This paper cites RLAIF vs.

Contrastive Weak-to-strong Generalization RLAIF vs

Reference 18

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source=arxiv_source observed=2026-08-04T10:56:37.034365Z digest=sha256:08bb49de36c4bf3ba0d9e258e95d5beced3541697d8f7edbebbe1e367297ce6b

Observation 57594bd1-0c0c-4f0a-9891-1937d44e3e1c · outbound

This paper cites Scalable agent alignment via reward modeling: a research direction.

Contrastive Weak-to-strong Generalization Scalable agent alignment via reward modeling: a research direction

Reference 19

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Observation 54fdf2cd-095e-4648-8f58-8eb2e51a44ed · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Contrastive Weak-to-strong Generalization From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 20

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Observation f7f05201-f978-4c64-ba0a-fbbfdbb93e9c · outbound

This paper cites Contrastive decoding: Open-ended text generation as optimization.

Contrastive Weak-to-strong Generalization Contrastive decoding: Open-ended text generation as optimization

Reference 21

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Observation ea3b51f2-d902-49bc-a250-38947680cd83 · outbound

This paper cites Strong empowered and aligned weak mastered annotation for weak-to-strong generalization.

Contrastive Weak-to-strong Generalization Strong empowered and aligned weak mastered annotation for weak-to-strong generalization

Reference 22

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source=arxiv_source observed=2026-08-04T10:56:37.377675Z digest=sha256:08b4de35a8a3e4214f2c0b3ec30553a187637021e4209f4349883ab6e47429e8

Observation 34d373b1-5442-4e1b-a924-255a09f88365 · outbound

This paper cites Truthfulqa: Measuring how models mimic human falsehoods.

Contrastive Weak-to-strong Generalization Truthfulqa: Measuring how models mimic human falsehoods

Reference 23

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Observation 963a2b5d-d1d2-4909-b684-32a08fd4e36d · outbound

This paper cites MACPO: weak-to-strong alignment via multi-agent contrastive preference optimization.

Contrastive Weak-to-strong Generalization MACPO: weak-to-strong alignment via multi-agent contrastive preference optimization

Reference 24

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source=arxiv_source observed=2026-08-04T10:56:37.506239Z digest=sha256:399126453dde47787545830301940e41adac90581e529b1762b5318c277d57e0

Observation 8d101127-054d-436e-ac3b-32e1e75b327a · outbound

This paper cites Simpo: Simple preference optimization with a reference-free reward.

Contrastive Weak-to-strong Generalization Simpo: Simple preference optimization with a reference-free reward

Reference 25

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Observation c0f52ddf-8b96-43da-b42a-b6f68e191ae2 · outbound

This paper cites an unresolved cited work.

Contrastive Weak-to-strong Generalization Unresolved cited work

Reference 26

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Observation 360e3fee-25da-4a5f-b656-3077c6cc3cd4 · outbound

This paper cites GPT-4 Technical Report.

Contrastive Weak-to-strong Generalization GPT-4 Technical Report

Reference 27

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Observation be834da6-4e7b-43dc-9bbe-a1ead39b9867 · outbound

This paper cites an unresolved cited work.

Contrastive Weak-to-strong Generalization Unresolved cited work

Reference 28

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Observation 6dac21e1-6ba1-4cd1-9b33-1d492b6ef1bb · outbound

This paper cites Manning, Stefano Ermon, and Chelsea Finn.

Contrastive Weak-to-strong Generalization Manning, Stefano Ermon, and Chelsea Finn

Reference 29

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Observation 60dca906-7e0c-4ea0-8da8-139c89a4b591 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Contrastive Weak-to-strong Generalization Proximal Policy Optimization Algorithms

Reference 30

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Observation 7df6a7ba-5ed1-4aae-a0bd-bf7125bf88f9 · outbound

This paper cites Large Language Model Alignment: A Survey.

Contrastive Weak-to-strong Generalization Large Language Model Alignment: A Survey

Reference 31

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Observation 30ef333d-eb7d-41fe-8eaf-38c6420a11ff · outbound

This paper cites A transfer learning framework for weak to strong generalization.

Contrastive Weak-to-strong Generalization A transfer learning framework for weak to strong generalization

Reference 32

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source=arxiv_source observed=2026-08-04T10:56:38.367594Z digest=sha256:1b450212ab4dcd0ece65af8563deb1404647336dee911b2d189041af48271789

Observation e5cbe709-d382-4368-aa4a-73c955ed2747 · outbound

This paper cites Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F.

Contrastive Weak-to-strong Generalization Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F

Reference 33

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Observation 7e176b35-60fd-44d7-bed4-4d9e42d77939 · outbound

This paper cites Eleutherai/lm-evaluation-harness: v0.4.3, July 2024.

Contrastive Weak-to-strong Generalization Eleutherai/lm-evaluation-harness: v0.4.3, July 2024

Reference 34

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Observation 525ae0b0-668f-4ecf-96ab-68ca928490f8 · outbound

This paper cites Interpretable preferences via multi-objective reward modeling and mixture-of-experts.

Contrastive Weak-to-strong Generalization Interpretable preferences via multi-objective reward modeling and mixture-of-experts

Reference 35

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Observation 90aba70e-51f0-4d8a-9cf8-6aaaa24c599b · outbound

This paper cites Qwen2.5 Technical Report.

Contrastive Weak-to-strong Generalization Qwen2.5 Technical Report

Reference 36

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Observation 22f4f29c-b901-4429-aa86-fca712088d66 · outbound

This paper cites Super(ficial)-alignment: Strong models may deceive weak models in weak-to-strong generalization.

Contrastive Weak-to-strong Generalization Super(ficial)-alignment: Strong models may deceive weak models in weak-to-strong generalization

Reference 37

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source=arxiv_source observed=2026-08-04T10:56:39.109506Z digest=sha256:e4d1d2db93233b0757a7ec6cbc9667a2c1be705375faa17deea6c09a62550cd0

Observation 0363d6e7-5c30-4ef6-8a20-7898b4a4b454 · outbound

This paper cites The Capabilities and Limitations of Weak-to-Strong Generalization: Generalization and Calibration.

Contrastive Weak-to-strong Generalization The Capabilities and Limitations of Weak-to-Strong Generalization: Generalization and Calibration

Reference 38

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Observation ce83bb69-ef87-45a4-a8f0-7df4b84074be · outbound

This paper cites Free Process Rewards without Process Labels.

Contrastive Weak-to-strong Generalization Free Process Rewards without Process Labels

Reference 39

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source=arxiv_source observed=2026-08-04T10:56:39.305067Z digest=sha256:f7de0f4c8e3ac9c489f32d4d65d8ab02dca42fdcb17e949016ac47077fc8707c

Observation bc53be10-ccfa-41e0-96e8-940cdf0fb801 · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In ACL (1) , pp.\ 4791--4800.

Contrastive Weak-to-strong Generalization Hellaswag: Can a machine really finish your sentence? In ACL (1) , pp.\ 4791--4800

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:39.457283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:39.457283Z digest=sha256:96f66c3f83f5dafac39962e3d5efa3c3491ca9fa9a52bc9fbc43572ef323f247

Observation 66fec589-19dc-4999-b23a-8aadeccacc50 · outbound

This paper cites Super Co-alignment of Human and AI for Sustainable Symbiotic Society.

Contrastive Weak-to-strong Generalization Super Co-alignment of Human and AI for Sustainable Symbiotic Society

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:39.608269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:39.608269Z digest=sha256:179b219d1f915315d6c58349988c09cc0e995fda9bc1a65b2f9d13a7f0752ca4

Observation ade56135-cbbd-41a3-817f-b1f29d7066e7 · outbound

This paper cites Alleviating Hallucinations of Large Language Models through Induced Hallucinations.

Contrastive Weak-to-strong Generalization Alleviating Hallucinations of Large Language Models through Induced Hallucinations

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:39.738631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:39.738631Z digest=sha256:1697c67accf8fedfa3e5209a8ca99fa8fe6977bd77affe51a42bc94eb36bb661

Observation bc500c42-524f-4d63-a4d2-0c23adcb98c8 · outbound

This paper cites Emulated disalignment: Safety alignment for large language models may backfire! In ACL (1) , pp.\ 15810--15830.

Contrastive Weak-to-strong Generalization Emulated disalignment: Safety alignment for large language models may backfire! In ACL (1) , pp.\ 15810--15830

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:39.916024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:39.916024Z digest=sha256:d272c9a4e04d4d16cc64935ac6779d5afd33f3bcdddd01f1bf2a227521df6416

Observation 09dd1594-4bab-40a6-9d45-eb737314523a · outbound

This paper cites Weak-to-strong search: Align large language models via searching over small language models.

Contrastive Weak-to-strong Generalization Weak-to-strong search: Align large language models via searching over small language models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:40.085756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:40.085756Z digest=sha256:0729e5d023dc4fe333a5160db9c064826dae3f9cc8ef164fd81804841212a712

Observation 7c718e00-c3e6-448a-8ace-42d97f9e5015 · outbound

This paper cites Weak-to-strong preference optimization: Stealing reward from weak aligned model.

Contrastive Weak-to-strong Generalization Weak-to-strong preference optimization: Stealing reward from weak aligned model

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:40.223461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:40.223461Z digest=sha256:16e5db95f8523800a477d5c5ad126545e1e997b60c417f3e06d039d2df8ca733

Observation bd336af9-09c1-4d11-ba37-fb97164a2e62 · outbound

This paper cites write newline.

Contrastive Weak-to-strong Generalization write newline

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:40.403785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:40.403785Z digest=sha256:b82e9540c331dfaee2f520f4768171685fa9a6e1c00f4c28146f527de2698925

Observation cec06a70-335c-47ce-933d-c5979d6294b5 · outbound

This paper cites @esa (Ref.

Contrastive Weak-to-strong Generalization @esa (Ref

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:40.556702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:40.556702Z digest=sha256:598af33aac21c2d84b535e6893ff615b06f626023c61ae5f1a2cb28b514edd81

Observation 5a81682e-eaea-4ac5-a906-1d195366532a · outbound

This paper cites an unresolved cited work.

Contrastive Weak-to-strong Generalization Unresolved cited work

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:40.717856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:40.717856Z digest=sha256:16384ef4c4046b92f825ee9e4655a11637323f44a46dd7a814f229ce8e420825

Observation da11c7f1-93cc-4736-9b84-477819191c17 · outbound

This paper cites an unresolved cited work.

Contrastive Weak-to-strong Generalization Unresolved cited work

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-04T10:56:40.844714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:56:40.844714Z digest=sha256:ef94d7fdf00d2c235979538dec72e371a8831567e2bed38d049faf5c79e18a8a

Pith citing papers

No inbound Pith citation observations are available.