Paper Citation Record · LEDGER

Calibrating LLMs with Information-Theoretic Evidential Deep Learning

As of 9 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 4 inbound Pith citation observations for arXiv:2502.06351.

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

pith.paper-citation-record.v1
2502.06351 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:50:05.907947Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T16:59:43.458733Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:40:01.001636Z

Reference resolution

28 of 28 outbound references displayed

verified exact2
verified fuzzy14
unresolved10
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f44645b-211a-41a8-821c-5d34a2c731b4 · outbound

This paper cites In fact, the choice of the prior r(π ) is not unique.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning In fact, the choice of the prior r(π ) is not unique

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.115588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8252dd49-5c7a-4801-bb7b-6c89c1658f17 · outbound

This paper cites The Llama 3 Herd of Models.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning The Llama 3 Herd of Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.845342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee0bfb67-372b-4a25-850d-e77bce86904d · outbound

This paper cites Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.850931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41a3a394-c4d6-4098-9e02-6781b55f86b4 · outbound

This paper cites Mistral 7B.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Mistral 7B

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.855697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5f0d389-d224-4382-b43a-f2b7b29ae7b2 · outbound

This paper cites Kingma and Max Welling.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Kingma and Max Welling

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.210685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a589b0f-15e1-4a0c-bbaf-c6d686830e01 · outbound

This paper cites Can a suit of armor conduct elec- tricity? a new dataset for open book question answering.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Can a suit of armor conduct elec- tricity? a new dataset for open book question answering

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.188243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a1bd4621-cc98-44ed-8bd0-8e8b8b55337e · outbound

This paper cites Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.871043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba1e69b2-6e56-4fb5-a362-f51eda62ad8c · outbound

This paper cites Commonsenseqa: A question answering challenge targeting commonsense knowledge.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Commonsenseqa: A question answering challenge targeting commonsense knowledge

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.172025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ece08055-b5ab-42e9-9e7f-5f00a3593d7d · outbound

This paper cites If the calibration curve lies below the optimal diagonal line, it indicates that the model is ove rconﬁdent.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning If the calibration curve lies below the optimal diagonal line, it indicates that the model is ove rconﬁdent

Reference 17

Resolution: malformed identifier; raw_fallback, observed 2026-08-08T15:50:06.090064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c193d7b5-539a-4274-8bb6-2b91f7382ad9 · outbound

This paper cites Information robust dirichlet networks for predictive uncertainty estimation, April 8.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Information robust dirichlet networks for predictive uncertainty estimation, April 8

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.152218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 02811b7f-ce75-472e-8826-e069f9f88e21 · outbound

This paper cites BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.883949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60e8da2e-06b8-4349-ba0f-b1b734f0c2b2 · outbound

This paper cites To Believe or Not to Believe Your LLM.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning To Believe or Not to Believe Your LLM

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.889564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 725c77c4-f826-4503-9f41-a0db0daae5e9 · outbound

This paper cites (2017) as follows: I(Z,X ) = ∫ p(x, z) logp(z|x) p(z) dzdx = Ep(z|x)Ep(x)[logp(z|x)]− Ep(z)[logp(z)].

Calibrating LLMs with Information-Theoretic Evidential Deep Learning (2017) as follows: I(Z,X ) = ∫ p(x, z) logp(z|x) p(z) dzdx = Ep(z|x)Ep(x)[logp(z|x)]− Ep(z)[logp(z)]

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.134370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 15527b5c-f8e4-488d-b43f-f5016e77b1be · outbound

This paper cites (17) Plugging Eq.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning (17) Plugging Eq

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.123927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5f30fe0f-ca70-436b-9550-593add60cd8d · outbound

This paper cites LoRA hyperparameters: We applied LoRA (Hu et al.,.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning LoRA hyperparameters: We applied LoRA (Hu et al.,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.106745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7f4f636e-815a-41ab-942e-e9f85e8281c9 · outbound

This paper cites lora only.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning lora only

Reference 27

Resolution: malformed identifier; raw_fallback, observed 2026-08-08T15:50:06.098318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation acd98100-589e-4bb5-8ca0-5b4db842a4d1 · outbound

This paper cites Uncertainty estimation by ﬁsher information-based evidential deep learning.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Uncertainty estimation by ﬁsher information-based evidential deep learning

Reference 1968

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.227147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f588da39-3b42-4053-a9ad-cc47993c45c3 · outbound

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

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 1999

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.878646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d9eb5fc-aefd-4f36-b772-db34bd4d580c · outbound

This paper cites A scal able laplace approximation for neural networks.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning A scal able laplace approximation for neural networks

Reference 2008

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.180628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 05a5fb22-66be-4481-b015-207a23d32071 · outbound

This paper cites Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-08T15:50:06.053700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0d10a8be-d5b0-473b-9650-87c1db6e26cd · outbound

This paper cites Mixlora : Enhancing large language models ﬁne-tuning with lora-based mixture of experts, 2024.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Mixlora : Enhancing large language models ﬁne-tuning with lora-based mixture of experts, 2024

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.195429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a6a6a290-f3a1-4434-834a-525d3604d594 · outbound

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

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.834563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c64f6b95-b33f-4849-b9b0-b22ded547c42 · outbound

This paper cites Deep learning and the inf ormation bottleneck principle.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Deep learning and the inf ormation bottleneck principle

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.162503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 75aeb3dc-d3c8-457f-bd44-77b9b9657411 · outbound

This paper cites Transformers: State-of-the-art natural language processing.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Transformers: State-of-the-art natural language processing

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.143139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 17d789ac-e0f2-48fc-ae99-1493eb7db6dc · outbound

This paper cites RACE: Large-scale ReAding comprehension dataset from examinations.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning RACE: Large-scale ReAding comprehension dataset from examinations

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:50:06.202277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d2120118-1720-48fc-a01c-7cd9da884f2f · outbound

This paper cites Andrew Jesson, Nicolas Beltran-V elez, Quentin Chu, Sweta K arlekar, Jannik Kossen, Y arin Gal, John P Cunningham, and David Blei.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Andrew Jesson, Nicolas Beltran-V elez, Quentin Chu, Sweta K arlekar, Jannik Kossen, Y arin Gal, John P Cunningham, and David Blei

Reference 2022

Resolution: verified exact; raw_fallback, observed 2026-08-08T15:50:06.030296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2fb1be54-60a7-45c5-bfbd-d9e1d29217ff · outbound

This paper cites an unresolved cited work.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-08T15:50:06.219797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f1b60d10-4fcb-450f-8947-f4348ee1dc29 · outbound

This paper cites A Variational Dirichlet Framework for Out-of-Distribution Detection.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning A Variational Dirichlet Framework for Out-of-Distribution Detection

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T15:50:05.829495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 76316543-b521-4d80-985e-390156586b67 · inbound

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation cites this paper.

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation Calibrating LLMs with Information-Theoretic Evidential Deep Learning

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:55:59.614898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b43581b7-738a-4668-acd7-57c9c4157746 · inbound

Rethinking Vacuity for OOD Detection in Evidential Deep Learning cites this paper.

Rethinking Vacuity for OOD Detection in Evidential Deep Learning Calibrating LLMs with Information-Theoretic Evidential Deep Learning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:16:09.023388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8dbe2ed9-9bec-45f2-b6c1-3fac31977cdb · inbound

What Intermediate Layers Know: Detecting Jailbreaks from Entropy Dynamics cites this paper.

What Intermediate Layers Know: Detecting Jailbreaks from Entropy Dynamics Calibrating LLMs with Information-Theoretic Evidential Deep Learning

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T17:40:01.003247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3036f3a0-9f1a-4a3e-b632-7ca30458a6cd · inbound

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation cites this paper.

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation Calibrating LLMs with Information-Theoretic Evidential Deep Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:08:42.871021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.