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Paper Citation Record · LEDGER

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion

As of 16 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2505.07528.

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

pith.paper-citation-record.v1
2505.07528 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:18:57.034972Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

66 of 66 outbound references displayed

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  • verified fuzzy20
  • unresolved45
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation e8b02096-e7d2-4404-80a7-1596ce8d4dd9 · outbound

This paper cites Claude 3.7 sonnet: Hybrid reasoning model, state-of-the-art coding skills, computer use, and 200k context window, 2025.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Claude 3.7 sonnet: Hybrid reasoning model, state-of-the-art coding skills, computer use, and 200k context window, 2025

Reference 1

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0fdb43b6-9cc7-4543-a6c1-6dc45d583a89 · outbound

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

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion The Internal State of an LLM Knows When It's Lying

Reference 2

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source=pdf_text observed=2026-08-15T22:18:55.803445Z digest=sha256:36d1135938b0050d39f08e4cee27b63711daba203787a838eb1ff222b270f5e6

Observation 8d2ead0b-f716-4ed8-85be-aef5d1f8fe7c · outbound

This paper cites Audio chord recognition with recurrent neural networks.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Audio chord recognition with recurrent neural networks

Reference 3

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raw_fallback, observed 2026-08-15T22:18:58.234199Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 259a97b7-080f-4783-8b07-4bcfbe963366 · outbound

This paper cites Routledge, 2017.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Routledge, 2017

Reference 4

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raw_fallback, observed 2026-08-15T22:18:58.222489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:55.873899Z digest=sha256:787809fb077ab51bb2e4f77a4491249d99d1dfc24e160585981c19ee98634eb0

Observation f4c39e73-14a0-4955-a22a-10e9333ef8a6 · outbound

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

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

Reference 5

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source=pdf_text observed=2026-08-15T22:18:55.877156Z digest=sha256:976fefb03c5424b947489cbb653ce8b2ca8fdc09fa7045ed485baa5f288b4277

Observation 1a17a650-ac3d-4328-95e3-c7da7762d72e · outbound

This paper cites ChromaDB: AI-native open-source embedding database.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion ChromaDB: AI-native open-source embedding database

Reference 6

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raw_fallback, observed 2026-08-15T22:18:58.212666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f35d44a6-2830-42cb-ab72-09d3a4f83748 · outbound

This paper cites How to remove or control confounds in predictive models, with applications to brain biomarkers.GigaScience, 11:giac014, 2022.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion How to remove or control confounds in predictive models, with applications to brain biomarkers.GigaScience, 11:giac014, 2022

Reference 7

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raw_fallback, observed 2026-08-15T22:18:58.201130Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:55.886031Z digest=sha256:2ff140b6fed2cfead7427e35da3650928702d87780928b8cb67be2394a3fded3

Observation 2e65878e-be1d-45fa-990d-24fbaf23c009 · outbound

This paper cites Deepseek-r1 release, 2025.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Deepseek-r1 release, 2025

Reference 8

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raw_fallback, observed 2026-08-15T22:18:58.187546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:55.889205Z digest=sha256:2416d442b92af28e68c9d8ac85ba59d53cc8d66abad342b44452f4a27c42b549

Observation d1f2547d-84fb-461c-8ffd-bc02216b6be5 · outbound

This paper cites A mathematical framework for transformer circuits.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion A mathematical framework for transformer circuits

Reference 9

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raw_fallback, observed 2026-08-15T22:18:58.175164Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:55.893134Z digest=sha256:1fb441fde478d9841b28aff31c03bdfde00bc8d4d01c915f8e030022bde982e7

Observation 130013a0-74ef-4bf8-88e7-db8896f6a4fc · outbound

This paper cites Ragas: Automated evaluation of retrieval augmented generation.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Ragas: Automated evaluation of retrieval augmented generation

Reference 10

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source=pdf_text observed=2026-08-15T22:18:55.895964Z digest=sha256:1c1c47a0f0ad0ca7326801cf5243382be93fdd52f9375eecfe58f3d218829f19

Observation 3ca87547-6bdc-4c46-815a-f05e9d545c68 · outbound

This paper cites A survey on rag meeting llms: Towards retrieval-augmented large language models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion A survey on rag meeting llms: Towards retrieval-augmented large language models

Reference 11

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source=pdf_text observed=2026-08-15T22:18:55.899292Z digest=sha256:efa2db9e6d58fae159f128b96ff6f50ed7ccb26fc7c7a1f44d7eb712ad88708c

Observation 0a1fb5c1-31a2-4fc1-b3ea-931af8b55412 · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630, 2024.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630, 2024

Reference 12

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Observation fe91fb74-de08-4c39-a398-ef746591b493 · outbound

This paper cites Information Flow Routes: Automatically Interpreting Language Models at Scale.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Information Flow Routes: Automatically Interpreting Language Models at Scale

Reference 13

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source=pdf_text observed=2026-08-15T22:18:55.958059Z digest=sha256:82f26b04ac294b04157ccf5e26b688068ee96ea94d3bc24d75889c5abdbd55da

Observation 9a808685-4c0c-40cf-ba41-2a6a9fcc6fe6 · outbound

This paper cites A primer on the inner workings of transformer-based language models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion A primer on the inner workings of transformer-based language models

Reference 14

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raw_fallback, observed 2026-08-15T22:18:58.101947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:55.961817Z digest=sha256:e672db2850335377f403ff3e90cbb3d892ad542aaa5422db72d501505581d313

Observation 39915e59-6aa8-430e-8e2b-eae4c23cc336 · outbound

This paper cites Costa-jussà.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Costa-jussà

Reference 15

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raw_fallback, observed 2026-08-15T22:18:58.090515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:55.966132Z digest=sha256:f87258710945b84bd393f4f2804dd8d4e63496d1c86bbc063c1de52bd81734ab

Observation 67f4fc22-eff9-4f11-8317-13c3be2df9c7 · outbound

This paper cites The Chronicles of RAG: The Retriever, the Chunk and the Generator.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion The Chronicles of RAG: The Retriever, the Chunk and the Generator

Reference 16

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Observation afa0780f-0959-4f02-8660-631d6a19d49d · outbound

This paper cites Peer review of gpt-4 technical report and systems card.PLOS digital health, 3(1):e0000417, 2024.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Peer review of gpt-4 technical report and systems card.PLOS digital health, 3(1):e0000417, 2024

Reference 17

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Observation b6a7948c-2c72-4474-9a31-88212a0e7ff3 · outbound

This paper cites Transformer Feed-Forward Layers Are Key-Value Memories.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Transformer Feed-Forward Layers Are Key-Value Memories

Reference 18

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source=pdf_text observed=2026-08-15T22:18:56.085588Z digest=sha256:26662ddf0cb04b8a386aae7e422940eb2b3cdac8c9a6cf36062c70a097b172c2

Observation b9635040-92e3-447c-a9e7-5cff8df10361 · outbound

This paper cites The Llama 3 Herd of Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion The Llama 3 Herd of Models

Reference 19

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source=pdf_text observed=2026-08-15T22:18:56.089679Z digest=sha256:4c70c3eeb9a3ff9dd2e1071485237422ebfca4bdf9c11bc62afd7618bb710e87

Observation c1c4439f-3bb8-4544-873c-73c65764cd8d · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Sequence Transduction with Recurrent Neural Networks

Reference 20

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source=pdf_text observed=2026-08-15T22:18:56.093610Z digest=sha256:c51e4df0991b72bdd2fa5fcf858f9be10a817a7a81c44cc7be89872b54148a56

Observation b9b828e8-0eef-414e-8e82-20f5d57e74b2 · outbound

This paper cites Inspecting and Editing Knowledge Representations in Language Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Inspecting and Editing Knowledge Representations in Language Models

Reference 21

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Observation 5c4c3be1-a461-426c-8e70-fd5242a40e44 · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43 (2):1–55, 2025.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43 (2):1–55, 2025

Reference 22

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.145529Z digest=sha256:58fe735fbdbc065f2b97806f0a818ce1879a4cba50fe5971781b2a13a83030e6

Observation 10f32b16-4c87-4ae1-ab6e-4b617b208123 · outbound

This paper cites To trust or not to trust? enhancing large language models’ situated faithfulness to external contexts.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion To trust or not to trust? enhancing large language models’ situated faithfulness to external contexts

Reference 23

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raw_fallback, observed 2026-08-15T22:18:57.988794Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.149156Z digest=sha256:f14a6e11c7be0eae98386030ccba76c7e5cf1606758d3454de061b95dc385334

Observation 856e4542-df0d-4854-819c-6254d9f24b21 · outbound

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

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Language Models (Mostly) Know What They Know

Reference 24

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source=pdf_text observed=2026-08-15T22:18:56.154518Z digest=sha256:10c90d01bd4ed2c223314dacc6b31ae878c110e2b070f3bb10a6421e3118e6de

Observation 6b22f5fb-d4a0-4d6d-a4b7-f69f40797ed7 · outbound

This paper cites Control of confounding in the analysis phase–an overview for clinicians.Clinical epidemiology, pages 195–204, 2017.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Control of confounding in the analysis phase–an overview for clinicians.Clinical epidemiology, pages 195–204, 2017

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.158459Z digest=sha256:e6391da1d17925cff6fa54b20d5a5d6eaa1df0df4dd9544e076ce3ec7c252652

Observation 34b25f62-41c8-4db6-a9be-ee9fbc4f86e1 · outbound

This paper cites Calibrated language models must hallucinate.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Calibrated language models must hallucinate

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.965090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.161621Z digest=sha256:b7bed7e936944849fe9b406712a1b4af1e9d8a6c54c5d6463ca9088c9dc3179d

Observation fa6660ff-394a-41c6-9ecb-bb57e7852527 · outbound

This paper cites Incorporating Residual and Normalization Layers into Analysis of Masked Language Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Incorporating Residual and Normalization Layers into Analysis of Masked Language Models

Reference 27

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source=pdf_text observed=2026-08-15T22:18:56.254476Z digest=sha256:a02cbb8bf8f7205d979a7ad8327f8c15632728b00afb500d202f82e8148a20de

Observation 6745185a-d31e-4215-b09e-2e28081613da · outbound

This paper cites Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs

Reference 28

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source=pdf_text observed=2026-08-15T22:18:56.290921Z digest=sha256:1ed9226ff7f1e61a3a62f7e4c0342dfa6d481422cec6a0c58b261400bc7a1e43

Observation 3afdb703-5f4a-4cc1-b65d-52759150136a · outbound

This paper cites Evaluating the Factual Consistency of Abstractive Text Summarization.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Evaluating the Factual Consistency of Abstractive Text Summarization

Reference 29

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source=pdf_text observed=2026-08-15T22:18:56.295101Z digest=sha256:4b6567cedc3eb88fd5d7cf560fe6d954b880fae4fe15243a735098c958f5dc25

Observation 6487bcb7-67de-4d45-b175-e474e34438e2 · outbound

This paper cites Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation

Reference 30

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source=pdf_text observed=2026-08-15T22:18:56.299950Z digest=sha256:80b66890c146f8de79692d297140b46a931782a66c632795cfa3b869edb24644

Observation b23d9b95-e18f-41a8-ab65-bc0acb83adfc · outbound

This paper cites Langchain is a framework for developing applications powered by large language models (llms).,.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Langchain is a framework for developing applications powered by large language models (llms).,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.927955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.304213Z digest=sha256:67708db87d7ff9220f31ffb4ef6d5dfdd90e05377814d5e99b012c5e764576e8

Observation 1d7f494b-6672-49b3-b10b-100aa62252a5 · outbound

This paper cites Look Within, Why LLMs Hallucinate: A Causal Perspective.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Look Within, Why LLMs Hallucinate: A Causal Perspective

Reference 32

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source=pdf_text observed=2026-08-15T22:18:56.312109Z digest=sha256:8bcec6a4ac949d5f5dae570734ccbb2f446dcb36e49f88b810342ab854a3c63a

Observation 8b57ff11-4370-4fda-9f2d-30fd562613bf · outbound

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

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Inference-time intervention: Eliciting truthful answers from a language model

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.897168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.345929Z digest=sha256:2e7c9a5249372866bc39dd0316e6c871e2f7bab63de5db6754b902105dd7f6fd

Observation a527ea8e-5ea9-413e-8b39-2ed05ecec9a4 · outbound

This paper cites DeepSeek-V3 Technical Report.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion DeepSeek-V3 Technical Report

Reference 34

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source=pdf_text observed=2026-08-15T22:18:56.405093Z digest=sha256:81f7a0b33defe396f2cbcc1b3a864c20169c3364a7437f6dd176dd11678bafda

Observation 1acde1b1-c901-46fe-8398-54f2f2792ca3 · outbound

This paper cites Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models

Reference 35

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source=pdf_text observed=2026-08-15T22:18:56.450677Z digest=sha256:eb1c21318bd370c76f436ca1e8f0c1b695dd35ec88917dfb8f50e4f1932ada38

Observation 644dd6a1-f018-4276-aa77-35e458af0167 · outbound

This paper cites Large Language Models as Foundations for Next-Gen Dense Retrieval: A Comprehensive Empirical Assessment.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Large Language Models as Foundations for Next-Gen Dense Retrieval: A Comprehensive Empirical Assessment

Reference 36

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source=pdf_text observed=2026-08-15T22:18:56.455695Z digest=sha256:609bacef1f2c1a6152d4232b41407cf3a5df5038be50e878beb4ec395cb0a340

Observation e3408453-67b4-45ae-abf5-cf573251aadc · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 37

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source=pdf_text observed=2026-08-15T22:18:56.460403Z digest=sha256:fcd1043865332161a1306f08e0b9fd8bf1743470a73896f3c0fab1dad1fdf32c

Observation efd05456-c356-41c4-b611-c6ddf59e0b8b · outbound

This paper cites Llama 2: open source, free for research and commercial use, 2023.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Llama 2: open source, free for research and commercial use, 2023

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.884715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.464700Z digest=sha256:d8c371bb8e6fd0974531d769ddcd7885e732bf09fdb6960943f1bad11df8f9c8

Observation 1bb7b653-eb80-43bc-8f3f-e20736906b77 · outbound

This paper cites Introducing Meta Llama 3: The most capable openly available LLM to date, 2024.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Introducing Meta Llama 3: The most capable openly available LLM to date, 2024

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.738918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.468628Z digest=sha256:9e2dbd497841880427314d1ca056d7a9d033b7de50b1b007c282fe0e3796a0db

Observation eca27e1c-e00c-4351-9574-cdcfe764aace · outbound

This paper cites FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Reference 40

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source=pdf_text observed=2026-08-15T22:18:56.472268Z digest=sha256:005490d0dd8041f53b2781a29c514280229fd554ae8b79d2a2d8fa5fc2ddf46d

Observation 81243e9a-94d1-476a-ac69-8518f2ebcf3b · outbound

This paper cites Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction

Reference 41

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verified exact
local_arxiv, observed 2026-08-15T22:18:57.321095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.547557Z digest=sha256:849b29be660f035a28e22ea1e30aebc98e6d6c569a1fe4779d108fb11a12bc7b

Observation 068ea40a-4032-47fe-8e9a-5319c1e5af94 · outbound

This paper cites RAGTruth: A hallucination corpus for developing trustworthy retrieval-augmented language models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion RAGTruth: A hallucination corpus for developing trustworthy retrieval-augmented language models

Reference 42

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.551924Z digest=sha256:f6e6a446ec53b5551ce69df1b41596f001825003183b2dae168064dc00c486a7

Observation c743dd55-bf7a-418a-8de3-ad190b91e21c · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 43

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source=pdf_text observed=2026-08-15T22:18:56.555152Z digest=sha256:dd8f7feec2f69ac0c93b2d83e392467ef0da453a080b45e1e80f755384bd59e8

Observation 7bd25916-a563-4167-8dfe-9bb64d8aa75b · outbound

This paper cites Improving language under- standing by generative pre-training.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Improving language under- standing by generative pre-training

Reference 44

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no resolver link, observed 2026-08-15T22:18:56.558896Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.558896Z digest=sha256:c58e82ee7b682a29f587e60c8d2c16b18e4f8d041a0272804d9077f64dc611f9

Observation 3386db0f-8a95-47e9-8aa4-11f93419c6a6 · outbound

This paper cites The HalluRAG Dataset: Detecting Closed-Domain Hallucinations in RAG Applications Using an LLM's Internal States.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion The HalluRAG Dataset: Detecting Closed-Domain Hallucinations in RAG Applications Using an LLM's Internal States

Reference 45

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.562587Z digest=sha256:19b3883d378a3e8975f2951501d05b37fd8ca282f7d209041e7361f090ec9d64

Observation ef90003c-9a00-4db3-b61f-c5e098c85e1e · outbound

This paper cites Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer

Reference 46

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no resolver link, observed 2026-08-15T22:18:56.586844Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.586844Z digest=sha256:dfa04d6e9d46ecac12bcac9071b132f93c6dc79a1f45663f838a255de143ff5d

Observation 07a510f6-6d55-4f53-9ab6-73b4a10226cc · outbound

This paper cites Extracting Latent Steering Vectors from Pretrained Language Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Extracting Latent Steering Vectors from Pretrained Language Models

Reference 47

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.629850Z digest=sha256:f2599e5be68625067725c524c284ce9263db5016d74cfe9dfecd8d9f6a5195a3

Observation b4dbfebd-174a-47de-8298-4ae1da55e7da · outbound

This paper cites Augmenting Self-attention with Persistent Memory.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Augmenting Self-attention with Persistent Memory

Reference 48

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.702059Z digest=sha256:f34b08fc1d597050ebeac54ae4a08445f265b3675cba36aca2032991381a349a

Observation e15249d5-4c4b-4a33-8c74-bdc654819c37 · outbound

This paper cites Transformer Layers as Painters.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Transformer Layers as Painters

Reference 49

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no resolver link, observed 2026-08-15T22:18:56.705729Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.705729Z digest=sha256:82b058abbcf17fbde4da4a178d972bf35475cb84a525944c1f6528e40ebd540a

Observation 6cd3dc83-b2d8-4a0d-95cc-d4424675515a · outbound

This paper cites Redeep: Detecting hallucination in retrieval-augmented generation via mechanistic interpretability.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Redeep: Detecting hallucination in retrieval-augmented generation via mechanistic interpretability

Reference 50

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.709900Z digest=sha256:2afa3dcadd6fd9a526971810758516c8be238ab67a901e63ef30509606b50b55

Observation 1518ad2a-7d61-4da7-aa21-a9656c99d839 · outbound

This paper cites Sequence to sequence learning with neural networks.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Sequence to sequence learning with neural networks

Reference 51

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no resolver link, observed 2026-08-15T22:18:56.715057Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.715057Z digest=sha256:ac3fc8f9abe909b843f36f9ea71ae084a27a22be68409a92f8fd527cc6029ba9

Observation 70a93df8-c574-4686-98c1-54a7de835446 · outbound

This paper cites Qwen2.5: A party of foundation models!, 2024.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Qwen2.5: A party of foundation models!, 2024

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.716241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.718371Z digest=sha256:e91c63393a70133fbd972de12a9fc05ec0bdb82c741eb098e99752075a0a1328

Observation 74fa9150-7633-4f2b-8160-d10a81f08eec · outbound

This paper cites The best 7b model to date, apache 2.0, 2024.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion The best 7b model to date, apache 2.0, 2024

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.672420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.763438Z digest=sha256:058d15e50171cec1c90365ab9c47d87c0fee774332f5fda48c9e6026bc17e9b7

Observation 0d21a7dc-c2cc-45bc-b0e1-0539e9190df8 · outbound

This paper cites A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 54

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.833963Z digest=sha256:9481c9cff565765abc8688725d783f98b9ac66c5a17bb6cf872d30581fae46ae

Observation 94481572-c72d-4020-a99d-e996ef94c196 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 55

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source=pdf_text observed=2026-08-15T22:18:56.844818Z digest=sha256:329858ed7fd444737ea04e6db3dab18732d89efcddeb7f9f13b5a673caee6c84

Observation 679f56a0-d2f8-4624-a36d-2f42a9f0a6bb · outbound

This paper cites Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned

Reference 56

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no resolver link, observed 2026-08-15T22:18:56.848801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:56.848801Z digest=sha256:35b40dcdf39bb5601a2a1c73fa738ccd9ad2a1d1450955fc10acc31ca570880c

Observation 609f3348-1edc-4c9d-9d06-115de20c88c5 · outbound

This paper cites Wise: Rethinking the knowledge memory for lifelong model editing of large language models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Wise: Rethinking the knowledge memory for lifelong model editing of large language models

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:18:57.504286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.854115Z digest=sha256:509e323fd480e74843ecf38ae12b26d7b96c994be91cc0be8d98898983cf138f

Observation 94619282-1e4e-48cd-8940-8dba8f746f5f · outbound

This paper cites Retrieval Head Mechanistically Explains Long-Context Factuality.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Retrieval Head Mechanistically Explains Long-Context Factuality

Reference 58

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no resolver link, observed 2026-08-15T22:18:56.859224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:56.859224Z digest=sha256:4030e7c6c9cf600110923d1f2cc90aca739dc8dbc91ee0f9964e195e50059989

Observation 3e8da0e0-97a8-4b74-86a9-c642463cd5ac · outbound

This paper cites Ragtruth: A hallucination corpus for developing trustworthy retrieval-augmented language models, 2023.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Ragtruth: A hallucination corpus for developing trustworthy retrieval-augmented language models, 2023

Reference 59

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no resolver link, observed 2026-08-15T22:18:56.863539Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T22:18:56.863539Z digest=sha256:2e4322ca78e25e6b8233ac25826158a829bbaaf0662ba07d53f6afaa39b629ed

Observation e13741d4-cf4d-4c1d-98fb-32bc6c1872c8 · outbound

This paper cites Knowledge Conflicts for LLMs: A Survey.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Knowledge Conflicts for LLMs: A Survey

Reference 60

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no resolver link, observed 2026-08-15T22:18:56.941850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:56.941850Z digest=sha256:76fa023bef1464f82783e212f067cf07f86e5c9812826f26a00505cdd8a71c3d

Observation 8a701dfc-5cf1-4072-a961-75053956ad68 · outbound

This paper cites Cognitive Mirage: A Review of Hallucinations in Large Language Models.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Cognitive Mirage: A Review of Hallucinations in Large Language Models

Reference 61

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no resolver link, observed 2026-08-15T22:18:57.018155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:57.018155Z digest=sha256:8817a694623a4427f67ba5a68885e9e618d8bb8e882609f0d35d7531e74656d4

Observation 0bad0e04-9b94-47ba-bee5-f8d7a840385f · outbound

This paper cites InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers

Reference 62

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no resolver link, observed 2026-08-15T22:18:57.021763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:57.021763Z digest=sha256:fcd982c1e02d393b961ebb7e73d8d438d516bd7d882d43475c66f7d1da8e3c56

Observation 265c1edc-c77e-4d95-97f3-efe22d4c161b · outbound

This paper cites Explainability for large language models: A survey.ACM Transactions on Intelligent Systems and Technology, 15(2):1–38, 2024.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Explainability for large language models: A survey.ACM Transactions on Intelligent Systems and Technology, 15(2):1–38, 2024

Reference 63

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no resolver link, observed 2026-08-15T22:18:57.026584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:57.026584Z digest=sha256:db6e0157bbabff0942a05b8d0f55c2fcfd1f3d404eb21c1ce6341e0c66690b35

Observation 2569a1a7-b213-465e-87d6-c5f9981716f6 · outbound

This paper cites Self-Adjust Softmax.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Self-Adjust Softmax

Reference 64

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no resolver link, observed 2026-08-15T22:18:57.031190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:57.031190Z digest=sha256:9d94902ed2fd1a9756c84806e898ce425a22eb1260d1206818ddddd7903fe80c

Observation fa57f143-9327-42c7-a785-ba0ce64e230a · outbound

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

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Representation Engineering: A Top-Down Approach to AI Transparency

Reference 65

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no resolver link, observed 2026-08-15T22:18:57.034972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:18:57.034972Z digest=sha256:c3b649694f0f7fed825b17e02ba82a54d35a2632635871e22facb7e3e9f28123

Observation 8ba07860-de8c-43a3-8f5f-6a095dbe40f6 · outbound

This paper cites an unresolved cited work.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Unresolved cited work

Reference 2025

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unresolved
raw_fallback, observed 2026-08-15T22:18:57.908535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:18:56.308172Z digest=sha256:557df180398eab5c84af5a6e4c8a8c20ee51ff21affc42ce02a695cb3cbd5a5f

Pith citing papers

No inbound Pith citation observations are available.