Paper Citation Record · LEDGER

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare

As of 18 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2509.04482.

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

pith.paper-citation-record.v1
2509.04482 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:17:35.985989Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T10:51:19.555985Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:53:13.299767Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy12
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation beae96a3-a022-4570-96c7-fb72892a5ddc · outbound

This paper cites In: Advances in Neural Information Processing Systems (NeurIPS), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Advances in Neural Information Processing Systems (NeurIPS), pp

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:17:39.018105Z

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Observation 8aa25dec-f652-4587-b837-def67d484da8 · outbound

This paper cites Nature Medicine29, 1930– 1940 (2023).

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Nature Medicine29, 1930– 1940 (2023)

Reference 2

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Observation 9ee6f4a4-fd05-462f-b27a-833acfa2e8ea · outbound

This paper cites Capabilities of GPT-4 on Medical Challenge Problems.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Capabilities of GPT-4 on Medical Challenge Problems

Reference 3

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Observation 62691237-a35c-43db-b331-ff36ca0bbe06 · outbound

This paper cites IEEE Transactions on Information Theory16(1), 41–46 (1970) https://doi.org/10.1109/TIT.1970.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare IEEE Transactions on Information Theory16(1), 41–46 (1970) https://doi.org/10.1109/TIT.1970

Reference 4

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Observation c838eb4d-bf62-44b4-9b0a-6320e7c11799 · outbound

This paper cites In: Advances in Neural Information Processing Systems, vol.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Advances in Neural Information Processing Systems, vol

Reference 5

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Observation bf58cd00-881a-4348-8f47-61c9270de299 · outbound

This paper cites Energy-based Out-of-distribution Detection.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Energy-based Out-of-distribution Detection

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T13:17:34.117847Z

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Observation 85f8335a-1f3e-4143-9d34-55c6167a4400 · outbound

This paper cites npj Women’s Health2(1), 26 (2024).

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare npj Women’s Health2(1), 26 (2024)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:17:38.330587Z

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Observation 2f64fc55-db7c-4d0d-894b-e39a846e11e5 · outbound

This paper cites an unresolved cited work.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Unresolved cited work

Reference 8

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Observation 63656904-0da5-4783-bb4f-2ac9d737749c · outbound

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Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Unresolved cited work

Reference 9

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Observation 3ce62820-4429-4b49-846a-c090f99a9b98 · outbound

This paper cites SelectiveNet: A Deep Neural Network with an Integrated Reject Option.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare SelectiveNet: A Deep Neural Network with an Integrated Reject Option

Reference 10

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Observation 5e7d75e9-23be-41d1-8c83-93a64582b82f · outbound

This paper cites On Calibration of Modern Neural Networks.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare On Calibration of Modern Neural Networks

Reference 11

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Observation 44f360a2-8d77-46ce-bbdb-a7105441caee · outbound

This paper cites A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 12

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Observation e1e84c20-50f5-47df-8b21-b3652aaf0194 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 13

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Observation ca0f1bef-836c-417a-ad6c-5582e4d01171 · outbound

This paper cites In: International Conference on Learning Representations (ICLR) (2018).https://openreview.net/forum?id=H1VGkIxRZ.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: International Conference on Learning Representations (ICLR) (2018).https://openreview.net/forum?id=H1VGkIxRZ

Reference 14

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Observation 58629f3b-b40c-4045-9688-c9c67f2b4ff6 · outbound

This paper cites A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

Reference 15

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Observation a1c4b0a2-e056-4051-8ace-7ce6da594072 · outbound

This paper cites an unresolved cited work.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Unresolved cited work

Reference 16

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Observation ce6cc5ea-2de8-4915-b975-314da5c84b95 · outbound

This paper cites Generalized Out-of-Distribution Detection: A Survey.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Generalized Out-of-Distribution Detection: A Survey

Reference 17

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Observation bc9a3451-ea6b-4e24-af81-56e79cc8f5bd · outbound

This paper cites Predicting Structured Data1, 1–59 (2006).

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Predicting Structured Data1, 1–59 (2006)

Reference 18

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Observation 1a27c2d0-249b-47ee-ad38-ee2e79538f04 · outbound

This paper cites Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One

Reference 19

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Observation a423d2db-67e8-472e-9b07-1ac514e89550 · outbound

This paper cites In: Proceedings of the 58th Annual Meeting of the Association for Computa- tional Linguistics (ACL), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Proceedings of the 58th Annual Meeting of the Association for Computa- tional Linguistics (ACL), pp

Reference 20

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Observation 972c8e0e-83a9-4ebe-a487-a76b67824d55 · outbound

This paper cites Language Models (Mostly) Know What They Know.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Language Models (Mostly) Know What They Know

Reference 21

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Observation 9e12223d-aa74-4f82-91a4-3750dda611e2 · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 22

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This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 23

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Observation e509dff7-acf1-47e0-afee-44e86c7c229e · outbound

This paper cites Sampling Matters in Deep Embedding Learning.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Sampling Matters in Deep Embedding Learning

Reference 24

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Observation b25c0037-d887-4182-80e8-09b9a91c8820 · outbound

This paper cites In Defense of the Triplet Loss for Person Re-Identification.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In Defense of the Triplet Loss for Person Re-Identification

Reference 25

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Observation aa047234-0093-4936-b92b-ad950f9b7565 · outbound

This paper cites In: Pro- ceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Pro- ceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp

Reference 26

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Observation d9449779-a530-4826-93c6-8ae70a7dc7bc · outbound

This paper cites In: International Conference on Learning Representations (2021).https://openreview.net/forum?id=zeFrfgyZln.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: International Conference on Learning Representations (2021).https://openreview.net/forum?id=zeFrfgyZln

Reference 27

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Observation efbe2289-4126-4543-af14-3e2614672a6e · outbound

This paper cites In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:17:37.333185Z

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Observation 224eb6ba-5e14-4d93-8dfb-bd42f8060e73 · outbound

This paper cites Artificial Intelligence in Medicine102, 101753 (2020).

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Artificial Intelligence in Medicine102, 101753 (2020)

Reference 29

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Observation b381edc0-431e-4423-bca0-7fe16117ea03 · outbound

This paper cites In: Proceed- ings of the Conference on Health, Inference, and Learning (CHIL), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Proceed- ings of the Conference on Health, Inference, and Learning (CHIL), pp

Reference 30

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This paper cites In: Proceedings of the 2016 Conference on Empir- ical Methods in Natural Language Processing (EMNLP), pp.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare In: Proceedings of the 2016 Conference on Empir- ical Methods in Natural Language Processing (EMNLP), pp

Reference 31

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Observation f161a1ac-a9d7-4059-bd18-b367e11cd98e · outbound

This paper cites Out-of-Distribution Detection with Deep Nearest Neighbors.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Out-of-Distribution Detection with Deep Nearest Neighbors

Reference 32

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Observation e820f744-1ace-4186-ac8b-dddaee9c57f6 · outbound

This paper cites MixMatch: A Holistic Approach to Semi-Supervised Learning.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare MixMatch: A Holistic Approach to Semi-Supervised Learning

Reference 33

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Observation d7ce5f52-0114-4aef-b563-007dca3d488a · outbound

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Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare Unresolved cited work

Reference 34

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Observation e04dd51e-9044-4259-a12f-6bc7943f4199 · outbound

This paper cites https://api.semanticscholar.org/CorpusID: 9540064.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare https://api.semanticscholar.org/CorpusID: 9540064

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:17:36.760800Z

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Observation f51f193d-c049-4140-bf7c-d13fec65df77 · outbound

This paper cites MedGemma Technical Report.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare MedGemma Technical Report

Reference 36

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Observation 0bd3c73f-d1d4-4afc-88ae-534447861b47 · outbound

This paper cites The Faiss library.

Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare The Faiss library

Reference 37

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Pith citing papers

Observation ec529db9-83c1-40f9-9efc-b2619af5715a · inbound

Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents cites this paper.

Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:53:13.301454Z

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