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Paper Citation Record · LEDGER

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering?

As of 23 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2506.16450.

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

pith.paper-citation-record.v1
2506.16450 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:42:06.034751Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T19:05:26.015345Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T19:06:30.573744Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6205e0c4-e0c7-4c49-bbed-32e6cdeb5802 · outbound

This paper cites In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:04.642963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:04.642963Z digest=sha256:174c1a4c5c8629cef4cee8901910632f936c0303d4d12d63430d082d003b6031

Observation 66e37649-9b95-4238-ac0f-2a53b3d1b8c1 · outbound

This paper cites In: CVPR (2024).

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? In: CVPR (2024)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:08.394271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T23:42:04.817798Z digest=sha256:0c46b9f79413b63ed812cdb99fa2064e889ec8811c76b9982c92a647618f2a1e

Observation 332f8ec2-52c3-4a17-829d-c8407ccc136e · outbound

This paper cites Streaming Video Question-Answering with In-context Video KV-Cache Retrieval.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Streaming Video Question-Answering with In-context Video KV-Cache Retrieval

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:04.915126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:04.915126Z digest=sha256:f452a5e2e5a8d16be34418c8b36b7c36d88d0bad3dfbd0019826f7fdb64a44c0

Observation ff9fe540-7453-4998-ad20-ed4b7f01a12c · outbound

This paper cites Ego4D: Around the World in 3,000 Hours of Egocentric Video.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Ego4D: Around the World in 3,000 Hours of Egocentric Video

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:05.007036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:05.007036Z digest=sha256:8478e15808676235aa5b6ed64a565d76b49dcb8d7568485efb7e26bdc582a80a

Observation 02b69ca2-102c-4252-afca-d18c13e564fa · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? LLaVA-OneVision: Easy Visual Task Transfer

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:05.115153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:05.115153Z digest=sha256:d64c2f996768663ba25c36b2411f34b74cd211de6ee7cf5dca17635f910be5eb

Observation 180a0352-b7fc-4242-a611-0101eb465c70 · outbound

This paper cites an unresolved cited work.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:42:08.105399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T23:42:05.264823Z digest=sha256:66e87e1390192b7f66e179ccf6db75b276dc46a979bf2ae96ec716c3fe023204

Observation a6d2109a-789d-4567-8e50-0c1ac1c10770 · outbound

This paper cites an unresolved cited work.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:42:07.913445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T23:42:05.354757Z digest=sha256:9f0d7a38498edbc3f450698066d61d2b95c7bc2145e8d260e083956310157477

Observation aa21bac2-c9d8-4880-a8c6-06e7f268ed7b · outbound

This paper cites In: Ranzato, M., Beygelz- imer, A., Dauphin, Y., Liang, P., Vaughan, J.W.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? In: Ranzato, M., Beygelz- imer, A., Dauphin, Y., Liang, P., Vaughan, J.W

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:07.607242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T23:42:05.526632Z digest=sha256:3b7e647c21fbb09174fc89b25ebd3eb0ccd5589c80f966d35824d7401c924fa5

Observation ddf64084-04f4-4260-8389-fbef50ca85f4 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Gemini: A Family of Highly Capable Multimodal Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:05.672849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:05.672849Z digest=sha256:1f207f786c3f637fbdbfef068842b10d5ce00b16ee6f21676b1a36a5df6c98e1

Observation cee4710b-13fa-45cc-ab82-6ad0f304e978 · outbound

This paper cites Organization of memory1(381- 403), 1 (1972).

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Organization of memory1(381- 403), 1 (1972)

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:07.352929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T23:42:05.801135Z digest=sha256:aaf41caad8b527dce62ddd385768a62752a0711edeb07771ccbd8263d327cfe1

Observation 26244bf5-0094-4a2f-a175-3efb65d83ac2 · outbound

This paper cites InternVideo2: Scaling Foundation Models for Multimodal Video Understanding.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? InternVideo2: Scaling Foundation Models for Multimodal Video Understanding

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:05.964749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:05.964749Z digest=sha256:f2d28a6e3af0fd0ae56cd7aa6df25bcd62df12c404f2c68d3b754b60aa56bd9e

Observation 585a0189-6a6c-4ccb-9797-a06ce8452a52 · outbound

This paper cites an unresolved cited work.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:05.998084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:05.998084Z digest=sha256:3de9e483f2c7b77ea5d7d5eae97bdc37924e9beddec4e228c0433dc9dbe14711

Observation e4b3c3df-9f57-4003-a1f1-73aab35ad4f2 · outbound

This paper cites VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T23:42:06.011626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:42:06.011626Z digest=sha256:f908be35966b618edfdf6997f1c68800e48ab09a255ee04f43efa658c775e3c9

Observation 61660969-f4d6-4453-a293-c4402d6c8a38 · outbound

This paper cites In: Forty-first International Conference on Machine Learning (2024),https://openreview.net/forum?id=FPlaQyAGHu.

How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering? In: Forty-first International Conference on Machine Learning (2024),https://openreview.net/forum?id=FPlaQyAGHu

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:07.116018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T23:42:06.034751Z digest=sha256:b7c86f990c6c723570ed2e48f3c07fbace4a51278b7bf15e0ce3450e0a130942

Pith citing papers

Observation 63c24f57-0046-4c73-84e3-e6dc721fa729 · inbound

Exploring Multimodal LMMs for Online Episodic Memory Question Answering on the Edge cites this paper.

Exploring Multimodal LMMs for Online Episodic Memory Question Answering on the Edge How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering?

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:06:30.576722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:05:26.015345Z digest=sha256:4200d9205e7a934e7eed83a69ddaec01018fd1f8120dce93e46cb27addb8ecb4