Paper Citation Record · LEDGER

TruthFlow: Truthful LLM Generation via Representation Flow Correction

As of 9 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 4 inbound Pith citation observations for arXiv:2502.04556.

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

pith.paper-citation-record.v1
2502.04556 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:23:28.738176Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:48.011356Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

59 of 59 outbound references displayed

verified exact1
verified fuzzy8
unresolved50
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation a2864384-b0f7-47c7-bbdf-2082d5fbefd4 · outbound

This paper cites GPT-4 Technical Report.

TruthFlow: Truthful LLM Generation via Representation Flow Correction GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.192931Z

Source-reported events for the cited work

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Observation 3818e60a-cff0-4246-b839-04b28c61f2ec · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.254012Z

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Observation e24c2f5f-b285-484e-8858-4cf600f8fc70 · outbound

This paper cites The Internal State of an LLM Knows When It's Lying.

TruthFlow: Truthful LLM Generation via Representation Flow Correction The Internal State of an LLM Knows When It's Lying

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.320617Z

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Observation 3cdc8482-1021-4ae2-b7b5-63c2a1112dcf · outbound

This paper cites Qwen Technical Report.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Qwen Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.350971Z

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Observation 9c917423-b91d-4138-a46e-bc305100f03b · outbound

This paper cites F., Liu, X., Jagadish, H., and Wang, L.

TruthFlow: Truthful LLM Generation via Representation Flow Correction F., Liu, X., Jagadish, H., and Wang, L

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.561691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3b003863-bb5e-474e-8730-6778ee43d89f · outbound

This paper cites an unresolved cited work.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-08T22:23:29.487980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9dbca40c-cdbd-44d1-8860-f76e512d073c · outbound

This paper cites Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.362479Z

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Observation 0562b58a-3f5d-476b-87f7-72d7fd21ae64 · outbound

This paper cites Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.430340Z

Source-reported events for the cited work

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Observation 8f12cd1d-928d-4dad-8eb7-ce13dc188a92 · outbound

This paper cites Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.507483Z

Source-reported events for the cited work

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Observation 48e60b3d-9bdc-49ea-a7a6-ab95de8f0d4b · outbound

This paper cites INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection.

TruthFlow: Truthful LLM Generation via Representation Flow Correction INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.534094Z

Source-reported events for the cited work

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Observation fc1fb706-b76e-4937-9fcc-fd9c4400c00a · outbound

This paper cites Lower Layers Matter: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Lower Layers Matter: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-08T22:23:29.149431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation df555452-e19f-42d0-b783-2653d6ac2cba · outbound

This paper cites In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation.

TruthFlow: Truthful LLM Generation via Representation Flow Correction In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.541432Z

Source-reported events for the cited work

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Observation 0f2236e7-28e7-4254-bec9-28aa3f8d733f · outbound

This paper cites GRATH: Gradual Self-Truthifying for Large Language Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction GRATH: Gradual Self-Truthifying for Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.545341Z

Source-reported events for the cited work

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Observation 201869d0-430e-4dd7-9084-999be4ef0c05 · outbound

This paper cites Truth forest: Toward multi-scale truthfulness in large language models through intervention without tuning.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Truth forest: Toward multi-scale truthfulness in large language models through intervention without tuning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.477652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e289c78-b1fe-4411-ae9c-dc45a90603ba · outbound

This paper cites DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.687156Z

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Observation f68cfb77-be29-4af9-b752-46c146693ebb · outbound

This paper cites HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection.

TruthFlow: Truthful LLM Generation via Representation Flow Correction HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.744278Z

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Observation 787cb7f5-6728-4149-9707-f5c3d3763c73 · outbound

This paper cites The Llama 3 Herd of Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction The Llama 3 Herd of Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.754085Z

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Observation 6c11c963-594f-4313-bb89-20419926711c · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Scaling rectified flow transformers for high-resolution image synthesis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.758535Z

Source-reported events for the cited work

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Observation 83ad5505-3f12-4c00-bfce-1b79a568c449 · outbound

This paper cites Institutionum calculi integralis, volume 4.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Institutionum calculi integralis, volume 4

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.460372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 09f6ea34-236b-41c8-acbc-548facdc5fc8 · outbound

This paper cites Non-Linear Inference Time Intervention: Improving LLM Truthfulness.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Non-Linear Inference Time Intervention: Improving LLM Truthfulness

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.765808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3af8d04-62d3-4be0-b553-0a72efb441f8 · outbound

This paper cites Mitigating Large Language Model Hallucination with Faithful Finetuning.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.819703Z

Source-reported events for the cited work

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Observation 68c342f0-6d71-40c0-bfc1-b1ef84d71f66 · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.

TruthFlow: Truthful LLM Generation via Representation Flow Correction A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.915938Z

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Observation a7f212f7-7f0f-4b11-a696-c8e4635fd91f · outbound

This paper cites J., Madotto, A., and Fung, P.

TruthFlow: Truthful LLM Generation via Representation Flow Correction J., Madotto, A., and Fung, P

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.954263Z

Source-reported events for the cited work

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Observation c86aba22-2696-4246-9a7f-c28467b2237c · outbound

This paper cites Mistral 7B.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Mistral 7B

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.962031Z

Source-reported events for the cited work

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Observation d4480f36-b2cd-493f-bf97-3b06d174a7db · outbound

This paper cites Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.966500Z

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Observation b3e1e005-5edf-4283-ae6e-3b368ca8b285 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

TruthFlow: Truthful LLM Generation via Representation Flow Correction TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.970336Z

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Observation b4a7d798-0b2a-4103-adad-0731163b13f0 · outbound

This paper cites SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully.

TruthFlow: Truthful LLM Generation via Representation Flow Correction SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:27.974474Z

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Observation b918dc1f-940b-4089-a7b8-07212c30b8a9 · outbound

This paper cites Beitrag zur n \"a herungsweisen Integration totaler Differentialgleichungen.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Beitrag zur n \"a herungsweisen Integration totaler Differentialgleichungen

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.436488Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7b0c6773-0735-415f-8ee4-8b872093c1e2 · outbound

This paper cites Natural questions: a benchmark for question answering research.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Natural questions: a benchmark for question answering research

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.426143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6ca2f42b-d331-4589-86bd-2e4ab0f39882 · outbound

This paper cites u ttler, H., Lewis, M., Yih, W.-t., Rockt \.

TruthFlow: Truthful LLM Generation via Representation Flow Correction u ttler, H., Lewis, M., Yih, W.-t., Rockt \

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.171509Z

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Observation ba465a51-296c-4227-881a-eef3ca3c7eed · outbound

This paper cites HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.190876Z

Source-reported events for the cited work

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Observation 07e814d5-44aa-43ba-a0b4-04dc2a809c0a · outbound

This paper cites Inference-time intervention: Eliciting truthful answers from a language model.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Inference-time intervention: Eliciting truthful answers from a language model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.199961Z

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Observation 0b112ed8-4537-4c86-8cbb-ec1d4b7b0808 · outbound

This paper cites Contrastive Decoding: Open-ended Text Generation as Optimization.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Contrastive Decoding: Open-ended Text Generation as Optimization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.203920Z

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Observation c2a72bfb-fe41-4d23-b752-3ca5ea9bc3c7 · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods.

TruthFlow: Truthful LLM Generation via Representation Flow Correction TruthfulQA: Measuring How Models Mimic Human Falsehoods

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.209103Z

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Observation b0733e87-75d2-4eaf-b163-0ad3baeb2e1e · outbound

This paper cites Flow Matching for Generative Modeling.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Flow Matching for Generative Modeling

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.212853Z

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Observation c04a9a4f-0fa6-42ba-ade7-812b9f983853 · outbound

This paper cites DeepSeek-V3 Technical Report.

TruthFlow: Truthful LLM Generation via Representation Flow Correction DeepSeek-V3 Technical Report

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.265727Z

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Observation 31112765-95d2-4c20-900e-0e8502bb4c9e · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.371568Z

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Observation ef38339d-0b30-41fa-b882-91079f074a33 · outbound

This paper cites Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.406670Z

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Observation d86a6608-8fc0-4e76-a084-e37eab375ce2 · outbound

This paper cites Probing llms for logical reasoning.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Probing llms for logical reasoning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.402763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4f19e940-c736-4ddf-a7e1-fcbdc487e549 · outbound

This paper cites Contrastive Decoding Improves Reasoning in Large Language Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Contrastive Decoding Improves Reasoning in Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.424314Z

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Observation be610d12-d9aa-4ca7-adf8-ce4398e469e0 · outbound

This paper cites Training language models to follow instructions with human feedback.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Training language models to follow instructions with human feedback

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.428397Z

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Observation 87436ef0-890a-4c96-becb-d13c5b1257e8 · outbound

This paper cites Med-HALT: Medical Domain Hallucination Test for Large Language Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Med-HALT: Medical Domain Hallucination Test for Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.432815Z

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Observation 91ac5a9d-a185-43c2-82d1-08e16e47ddbd · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Steering Llama 2 via Contrastive Activation Addition

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.437300Z

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Observation 597c427e-b712-4dba-8951-9fd641b294a8 · outbound

This paper cites D., Ermon, S., and Finn, C.

TruthFlow: Truthful LLM Generation via Representation Flow Correction D., Ermon, S., and Finn, C

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.441246Z

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Observation 46460980-2a9e-4f90-a1b3-e2035a6369c7 · outbound

This paper cites A Survey of Hallucination in Large Foundation Models.

TruthFlow: Truthful LLM Generation via Representation Flow Correction A Survey of Hallucination in Large Foundation Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.444572Z

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Observation 456845d6-660b-4a3c-930a-b9e16efecb11 · outbound

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TruthFlow: Truthful LLM Generation via Representation Flow Correction Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-08T22:23:29.375574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b5ad759b-1650-4294-b34c-c665fd51e3e2 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

TruthFlow: Truthful LLM Generation via Representation Flow Correction U-net: Convolutional networks for biomedical image segmentation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.451311Z

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Observation 0be1d27a-1b33-46ad-a09b-37d1f57a3e82 · outbound

This paper cites U ber die numerische aufl \.

TruthFlow: Truthful LLM Generation via Representation Flow Correction U ber die numerische aufl \

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.357856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation daac12ba-004d-42f7-9d22-8bc25331a672 · outbound

This paper cites BLEURT: Learning Robust Metrics for Text Generation.

TruthFlow: Truthful LLM Generation via Representation Flow Correction BLEURT: Learning Robust Metrics for Text Generation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.458217Z

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Observation a62c728a-fea2-4da8-aee2-f0ee5cc5c77d · outbound

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

TruthFlow: Truthful LLM Generation via Representation Flow Correction Gemma: Open Models Based on Gemini Research and Technology

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.462488Z

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Observation 4fe22985-3b68-4fd6-939a-1d25156a0fd1 · outbound

This paper cites Fine-tuning Language Models for Factuality.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Fine-tuning Language Models for Factuality

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.466620Z

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Observation 84c669bc-1a15-4dce-a263-8e05c6ab312a · outbound

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

TruthFlow: Truthful LLM Generation via Representation Flow Correction Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.470232Z

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Observation f93ee7fb-d2fb-444f-b33c-a001ece16d12 · outbound

This paper cites Attention is all you need.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Attention is all you need

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.500981Z

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Observation dccf0263-ad27-449d-9892-7fc9035d1282 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

TruthFlow: Truthful LLM Generation via Representation Flow Correction HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.556369Z

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Observation 190d6256-a71b-4efb-a652-648797113d44 · outbound

This paper cites TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space.

TruthFlow: Truthful LLM Generation via Representation Flow Correction TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.595116Z

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Unavailable: canonical work link unavailable.

Observation d18f4ee2-97aa-4236-892c-8cd7d6b99b47 · outbound

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

TruthFlow: Truthful LLM Generation via Representation Flow Correction Alleviating Hallucinations of Large Language Models through Induced Hallucinations

Reference 56

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Observation 4e2be219-7c2c-46d3-906e-f41177bee29e · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Representation Engineering: A Top-Down Approach to AI Transparency

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.678697Z

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Observation 7490333d-c274-4b8c-b62c-e5a8ccffff81 · outbound

This paper cites Z., Fredrikson, M., and Hendrycks, D.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Z., Fredrikson, M., and Hendrycks, D

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T22:23:29.295766Z

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Observation 83baf9cc-db12-4b9f-97b5-a837c9ef14fb · outbound

This paper cites write newline.

TruthFlow: Truthful LLM Generation via Representation Flow Correction write newline

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-08T22:23:28.738176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation cd4c73eb-1e49-4e00-918c-6c288c0a0a60 · inbound

Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning cites this paper.

Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning TruthFlow: Truthful LLM Generation via Representation Flow Correction

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:48.011356Z

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Observation 9a47c79d-66b7-49ac-9c4f-2ead060a57a0 · inbound

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing cites this paper.

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing TruthFlow: Truthful LLM Generation via Representation Flow Correction

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-16T08:17:36.552368Z

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Observation a1686da3-46da-49c8-8909-707253a82eef · inbound

Steer Like the LLM: Activation Steering that Mimics Prompting cites this paper.

Steer Like the LLM: Activation Steering that Mimics Prompting TruthFlow: Truthful LLM Generation via Representation Flow Correction

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T01:59:34.588602Z

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Observation 3d32d3e8-4142-44f1-b257-9eae980a5405 · inbound

Can Factual Opinions Be Edited (Manipulated) in Large Language Models? cites this paper.

Can Factual Opinions Be Edited (Manipulated) in Large Language Models? TruthFlow: Truthful LLM Generation via Representation Flow Correction

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:56:29.000039Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.