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Paper Citation Record · LEDGER

Multimodal Anomaly Detection with a Mixture-of-Experts

As of 22 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2506.19077.

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

pith.paper-citation-record.v1
2506.19077 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:42:46.751315Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

28 of 28 outbound references displayed

  • verified exact2
  • verified fuzzy16
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86bc9645-2fe1-4042-b996-e6c38f652c53 · outbound

This paper cites Anomaly detection: A survey,.

Multimodal Anomaly Detection with a Mixture-of-Experts Anomaly detection: A survey,

Reference 1

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unresolved
no resolver link, observed 2026-08-15T18:42:46.601182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.601182Z digest=sha256:db6cf7d20100e26fb8ed3261438eb4f6cad23b6d6d9ceb5355903da668c62730

Observation 3839c611-6a80-4a96-bdb2-7a71ebd3993b · outbound

This paper cites Collaborative programming of conditional robot tasks,.

Multimodal Anomaly Detection with a Mixture-of-Experts Collaborative programming of conditional robot tasks,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.357984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 62727a35-2817-4d7f-9628-b2b1d2aba87c · outbound

This paper cites Collabo- rative programming of robotic task decisions and recovery behaviors,.

Multimodal Anomaly Detection with a Mixture-of-Experts Collabo- rative programming of robotic task decisions and recovery behaviors,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.341782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.612401Z digest=sha256:800187fd677800ab22647df6d6b47af1da93994389b497e0745af6f908875bad

Observation a4d0a3ba-a8f5-4121-99c6-63631afc11b5 · outbound

This paper cites Intuitive programming of con- ditional tasks by demonstration of multiple solutions,.

Multimodal Anomaly Detection with a Mixture-of-Experts Intuitive programming of con- ditional tasks by demonstration of multiple solutions,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.325922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.617521Z digest=sha256:14728c5195455996e7bace8a9bfdd938396b8fcdda61401ae5a7d78c05c41a2a

Observation 864f494c-dc64-47a4-b75c-92d80d89eb86 · outbound

This paper cites Anomaly detection for insertion tasks in robotic assembly using gaussian process models,.

Multimodal Anomaly Detection with a Mixture-of-Experts Anomaly detection for insertion tasks in robotic assembly using gaussian process models,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.310174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.623003Z digest=sha256:2df7e527914ec20d16fb204596605dd35c50f86f5027eae0450871669e0880bd

Observation 06e50e77-e1c1-4a4f-9f4b-82091d8306a4 · outbound

This paper cites Multimodal anomaly detection for assistive robots,.

Multimodal Anomaly Detection with a Mixture-of-Experts Multimodal anomaly detection for assistive robots,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.292375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.628060Z digest=sha256:5a66d01ac72ed37e8248e204e2c78cf9888ce1911bc2df1bd7809f6ec74cb221

Observation d7223471-bea9-4efd-9ad9-2273fa5159f9 · outbound

This paper cites Hmms for anomaly detection in autonomous robots,.

Multimodal Anomaly Detection with a Mixture-of-Experts Hmms for anomaly detection in autonomous robots,

Reference 7

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no resolver link, observed 2026-08-15T18:42:46.633529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.633529Z digest=sha256:b806a07954c2b0f6fccf451516a6130601b7f376a72bf30717da439ed32970a7

Observation 0b7876dd-e3d5-48ac-8ba7-0c4550991738 · outbound

This paper cites Conditionnet: Learning preconditions and effects for execution monitoring,.

Multimodal Anomaly Detection with a Mixture-of-Experts Conditionnet: Learning preconditions and effects for execution monitoring,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.266142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.639563Z digest=sha256:9f4776dd41f6e4c771b18bceb6e2ec7b55e8582d032aa43b0f961d6bed5c3bc3

Observation 9bffefd9-2b65-4d15-a7e3-1943d3dea8f1 · outbound

This paper cites A multimodal anomaly detector for robot-assisted feeding using an lstm-based variational autoen- coder,.

Multimodal Anomaly Detection with a Mixture-of-Experts A multimodal anomaly detector for robot-assisted feeding using an lstm-based variational autoen- coder,

Reference 9

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no resolver link, observed 2026-08-15T18:42:46.645066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.645066Z digest=sha256:b3eaf3d7bf236514bd522fde5aa2f9cd2e59290258b0ce82e5b69437d7bd7990

Observation 2a455fb0-fb58-40b6-96f0-27c283aa1ecb · outbound

This paper cites Multimodal anomaly detection based on deep auto-encoder for object slip perception of mobile manipulation robots,.

Multimodal Anomaly Detection with a Mixture-of-Experts Multimodal anomaly detection based on deep auto-encoder for object slip perception of mobile manipulation robots,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.239752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.649787Z digest=sha256:d53d9d9db86b2c3bfc566a4e4d093b401e37f348349b73c1aab1195a488e4a1c

Observation 47d1fe95-06bb-442c-b3fc-4efd26c455b2 · outbound

This paper cites Multimodal detection and classification of robot manipulation failures,.

Multimodal Anomaly Detection with a Mixture-of-Experts Multimodal detection and classification of robot manipulation failures,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.221160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a252886a-2cfc-49e8-9db5-d73f074bdf9c · outbound

This paper cites Clue-ai: A convolutional three-stream anomaly identification framework for robot manipulation,.

Multimodal Anomaly Detection with a Mixture-of-Experts Clue-ai: A convolutional three-stream anomaly identification framework for robot manipulation,

Reference 12

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unresolved
no resolver link, observed 2026-08-15T18:42:46.660876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.660876Z digest=sha256:fc50eca07686ca23e2afe44a552ab958726d1f4e38344368b44f4754f88f1d48

Observation e4d95f85-64af-4366-a962-b8a812b0db49 · outbound

This paper cites Robust, deep and in- ductive anomaly detection,.

Multimodal Anomaly Detection with a Mixture-of-Experts Robust, deep and in- ductive anomaly detection,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.193708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 00f45eb6-de79-421d-8ea3-882157a9fef7 · outbound

This paper cites Vision-language models as success detectors,.

Multimodal Anomaly Detection with a Mixture-of-Experts Vision-language models as success detectors,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.177680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.671495Z digest=sha256:07d8711e9eb234c3e0c7b0a534fd9e4d78f1662ad6b5a218d63805725384f37f

Observation ddfdc757-05aa-436b-aa4f-80aeb9a60a01 · outbound

This paper cites Fino-net: A deep multimodal sensor fusion framework for manipulation failure detection,.

Multimodal Anomaly Detection with a Mixture-of-Experts Fino-net: A deep multimodal sensor fusion framework for manipulation failure detection,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.139653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.681459Z digest=sha256:0f48a7fa67954e0a8e775a045486bfa7c603ff8f98e9e45193914b89e09a338d

Observation ad88c057-3e29-4810-bd3b-e4588f0197a1 · outbound

This paper cites Grounding Classical Task Planners via Vision-Language Models.

Multimodal Anomaly Detection with a Mixture-of-Experts Grounding Classical Task Planners via Vision-Language Models

Reference 16

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unresolved
no resolver link, observed 2026-08-15T18:42:46.686882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.686882Z digest=sha256:8c6da7fc6eebf9b1d5a390cddd8d201df305b28c601538183a2986df43475e73

Observation 548d1a00-c272-487c-a4b0-e29aa51f5701 · outbound

This paper cites Real-Time Anomaly Detection and Reactive Planning with Large Language Models,.

Multimodal Anomaly Detection with a Mixture-of-Experts Real-Time Anomaly Detection and Reactive Planning with Large Language Models,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.120235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.694195Z digest=sha256:83946b86a0d58d346bf505334f585d9dbe76c7761d51034b84b1bc4fb08fb676

Observation 7f6cd483-1901-4abb-99fb-fe97586f36d5 · outbound

This paper cites Confidence-based policy learning from demonstration using gaussian mixture models,.

Multimodal Anomaly Detection with a Mixture-of-Experts Confidence-based policy learning from demonstration using gaussian mixture models,

Reference 18

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raw_fallback, observed 2026-08-15T18:42:47.100941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.700601Z digest=sha256:608e7adf3cd1fc15c0ff00159fb0ff31ed729d4718e68fc6c5ad5a453b55978e

Observation fd1bb439-0389-4a17-a08e-a69d177401ee · outbound

This paper cites Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress.

Multimodal Anomaly Detection with a Mixture-of-Experts Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress

Reference 19

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unresolved
no resolver link, observed 2026-08-15T18:42:46.707011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.707011Z digest=sha256:d9858f5b1c42f700a0b330042a82741472c6387136be8fde68a0b722e09dc645

Observation 2079e7c5-cdc5-44a7-93f6-1564463507c9 · outbound

This paper cites Autoencoder-based network anomaly detection,.

Multimodal Anomaly Detection with a Mixture-of-Experts Autoencoder-based network anomaly detection,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.082379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5de10a44-2922-4c32-a64a-ad243a2ca001 · outbound

This paper cites Mad-gan: Multi- variate anomaly detection for time series data with generative adversar- ial networks,.

Multimodal Anomaly Detection with a Mixture-of-Experts Mad-gan: Multi- variate anomaly detection for time series data with generative adversar- ial networks,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.063869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.718497Z digest=sha256:200b00a8fd4fad56fe180f10f00e3a813b77f3427e2e488db92efcf0b37ab4ce

Observation 832f0a2a-f971-41b2-9796-b93ac0b488c6 · outbound

This paper cites Pddl - the planning domain definition language,.

Multimodal Anomaly Detection with a Mixture-of-Experts Pddl - the planning domain definition language,

Reference 22

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no resolver link, observed 2026-08-15T18:42:46.724475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.724475Z digest=sha256:7b8f04754708c85982b39259309463394cb99a12e8846a204aeb42325b218d86

Observation 64107d04-92d0-411b-bef9-2b297f4e4d73 · outbound

This paper cites Incremental kinesthetic teaching of motion primitives using the motion refinement tube,.

Multimodal Anomaly Detection with a Mixture-of-Experts Incremental kinesthetic teaching of motion primitives using the motion refinement tube,

Reference 23

Resolution
verified exact
doi, observed 2026-08-15T18:42:46.823370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.730444Z digest=sha256:e9180670ad8f590986f81b112c51f0778ebbbc1e7ef65ac31e2b8ad1f019b9bf

Observation 22fe6525-68bc-49f4-be62-add558c169d6 · outbound

This paper cites REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly.

Multimodal Anomaly Detection with a Mixture-of-Experts REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly

Reference 24

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unresolved
no resolver link, observed 2026-08-15T18:42:46.735349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.735349Z digest=sha256:3106cf88b2e2bf164df2b142b4cdcda50265f0705bf7175216e4890ca1c306f2

Observation 7644605f-0510-4dab-9106-26a370b82395 · outbound

This paper cites Invariant description of rigid body motion trajectories,.

Multimodal Anomaly Detection with a Mixture-of-Experts Invariant description of rigid body motion trajectories,

Reference 25

Resolution
verified exact
doi, observed 2026-08-15T18:42:46.805839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7544e250-99f6-4ea2-9cbe-2025be086082 · outbound

This paper cites Dynamic movement primitives in robotics: A tutorial survey,.

Multimodal Anomaly Detection with a Mixture-of-Experts Dynamic movement primitives in robotics: A tutorial survey,

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T18:42:46.746374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:42:46.746374Z digest=sha256:0ab7e77e8f2c02906467405fe301e711a1fe432328754751c25859f3adf16f5c

Observation 8da4e759-08c4-4ff8-b199-6fd198f0993e · outbound

This paper cites Multi-level task learning based on intention and constraint inference for autonomous robotic manipulation,.

Multimodal Anomaly Detection with a Mixture-of-Experts Multi-level task learning based on intention and constraint inference for autonomous robotic manipulation,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:42:47.035891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T18:42:46.751315Z digest=sha256:73e4016203348f8302a77572b1cea448ba27cb9cf9df8f2a431f933683bb7704

Observation ced1b690-0e5e-4050-9d55-55377581d1ba · outbound

This paper cites an unresolved cited work.

Multimodal Anomaly Detection with a Mixture-of-Experts Unresolved cited work

Reference 232

Resolution
unresolved
raw_fallback, observed 2026-08-15T18:42:47.158947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.