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Paper Citation Record · LEDGER

PEVLM: Parallel Encoding for Vision-Language Models

As of 21 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2506.19651.

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

pith.paper-citation-record.v1
2506.19651 v3

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:37:59.095922Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:17:09.834609Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:05:57.990017Z

Reference resolution

36 of 36 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ec57643b-5e59-4896-b366-58d4b9bcd0ad · outbound

This paper cites B.; et al.

PEVLM: Parallel Encoding for Vision-Language Models B.; et al

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:37:59.682739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:58.909204Z digest=sha256:b8d938e4891f5640dd21ac3dd16b2a646c66bccb35b2edc73e05973c499f9a98

Observation 5f897db2-af70-433c-a4c6-a181d7c13640 · outbound

This paper cites Qwen2.5-VL Technical Report.

PEVLM: Parallel Encoding for Vision-Language Models Qwen2.5-VL Technical Report

Reference 2

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no resolver link, observed 2026-08-15T18:37:58.914886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.914886Z digest=sha256:98d3c8d85d0fa7414984941415d5679516cb873758ef3d6f3a3a54c419dfa223

Observation 1086f908-087d-408d-96de-04d10a8cb811 · outbound

This paper cites E.; and Cohan, A.

PEVLM: Parallel Encoding for Vision-Language Models E.; and Cohan, A

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:58.920587Z digest=sha256:1381dde46c7aad09f71fb7d7afdf3921e50c5863ce9f0fa5499bfecbe5789473

Observation f6d3cc2e-784e-4c7e-b42e-a8e4e127bff4 · outbound

This paper cites Metabolic scaling in small life forms.

PEVLM: Parallel Encoding for Vision-Language Models Metabolic scaling in small life forms

Reference 4

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no resolver link, observed 2026-08-15T18:37:58.926663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.926663Z digest=sha256:f992da48cdd232e45af8b0b468ae80355d5c56f73fd0978c3b46fd56bb0b5c9b

Observation bf0f0076-ed43-4747-bc76-3697aa73b40f · outbound

This paper cites Connection of event shapes to the heavy-flavor baryon enhancement.

PEVLM: Parallel Encoding for Vision-Language Models Connection of event shapes to the heavy-flavor baryon enhancement

Reference 5

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no resolver link, observed 2026-08-15T18:37:58.932723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.932723Z digest=sha256:70491506ee7850a4a43a47f330f87bb67184b33ec1b3201021ed3d8d21a7e2ea

Observation 6312f77f-ae96-41fb-9d8e-d037e8cc2d67 · outbound

This paper cites LongVILA: Scaling Long-Context Visual Language Models for Long Videos.

PEVLM: Parallel Encoding for Vision-Language Models LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Reference 6

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no resolver link, observed 2026-08-15T18:37:58.938190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.938190Z digest=sha256:2ff367bb387a263712fd6b2ae823eb257ad5ea2603da10e8d4e36ef6375933f2

Observation 35d13144-643e-49da-844f-7de9ee9ae0b6 · outbound

This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.

PEVLM: Parallel Encoding for Vision-Language Models Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 7

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no resolver link, observed 2026-08-15T18:37:58.944133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.944133Z digest=sha256:958430e4aadb45c402331545d5a1b25fe6db2bdcc9f4c9f3e715e69ba631f292

Observation ff7d88f6-f4ac-4571-89a9-046c719473df · outbound

This paper cites The Kazdan-Warner problem on compact K\"ahler surfaces.

PEVLM: Parallel Encoding for Vision-Language Models The Kazdan-Warner problem on compact K\"ahler surfaces

Reference 8

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T18:37:58.949615Z digest=sha256:2ed6c75d2545dc13be950355a07652450bec5e53e65ca7d5ee9ff5bf972255b2

Observation 3402fc28-2d95-4ab3-987c-3ca56b4cf08d · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:58.955306Z digest=sha256:554d2b9e15daef2ac56880041b8aa3f23ff84a54374ae4ae291dfb30085abbf7

Observation cf558565-c28d-4480-b2ed-50195fabf28a · outbound

This paper cites Time-Transient Wireless RF Sensor with Differentiative Detecting Capability for Target Ionic Solution of Water and Dielectric Objects Introduced into Water.

PEVLM: Parallel Encoding for Vision-Language Models Time-Transient Wireless RF Sensor with Differentiative Detecting Capability for Target Ionic Solution of Water and Dielectric Objects Introduced into Water

Reference 10

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no resolver link, observed 2026-08-15T18:37:58.960310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.960310Z digest=sha256:44536a9420780167ad0daec5aa4f26a8264f219f2df313a6a86a5918a876516f

Observation e4086921-1ee2-4750-a572-0c1d470f44b9 · outbound

This paper cites See What You Are Told: Visual Attention Sink in Large Multimodal Models.

PEVLM: Parallel Encoding for Vision-Language Models See What You Are Told: Visual Attention Sink in Large Multimodal Models

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.965659Z digest=sha256:fc56bf175ca1ee60f2bfed3911b7a7ad745e5430c0d582dd323a85e86a9fc130

Observation 4e19a9ef-1022-4344-adc7-349a5b8eb20c · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

PEVLM: Parallel Encoding for Vision-Language Models Efficient Streaming Language Models with Attention Sinks

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.973138Z digest=sha256:ff4e4ab28ecd455811d0b8873850763cc7ef0e04582fb085c3875db197f3be27

Observation 8025eddb-a85d-4192-821f-14ec78e1d0cf · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 13

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raw_fallback, observed 2026-08-15T18:37:59.631881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:58.978954Z digest=sha256:4b90d20bc7137e8b9089c70215c96e235f44a499b5db2935d26173ec690c5c13

Observation d490d203-fc5f-444c-adb2-d1056550f63e · outbound

This paper cites MVBench: A Comprehensive Multi-modal Video Understanding Benchmark.

PEVLM: Parallel Encoding for Vision-Language Models MVBench: A Comprehensive Multi-modal Video Understanding Benchmark

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.984224Z digest=sha256:794ab263d31ef8fd39dc2c36d6512d2007f93719cb1fd332dfd05f18b53ea806

Observation ab0ca568-1ac7-49c2-8f74-1e19c24c80b9 · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 15

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raw_fallback, observed 2026-08-15T18:37:59.616422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:58.989674Z digest=sha256:f0536b9a7b294d5aa1258ba5f92e7d18b72bde0a916ec0bc2839ea717a3ab9a2

Observation 047844d6-371c-4d95-9b1d-ca8a9f38e047 · outbound

This paper cites FocusLLM: Precise Understanding of Long Context by Dynamic Condensing.

PEVLM: Parallel Encoding for Vision-Language Models FocusLLM: Precise Understanding of Long Context by Dynamic Condensing

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.994348Z digest=sha256:656b552a325f94e560670ace58840a72d8761f15a55cc2e744d226c5d411dba0

Observation d21233de-c0f6-4cd3-9114-462ba07ee34e · outbound

This paper cites F.; Lin, K.; Hewitt, J.; Paranjape, A.; Bevilacqua, M.; Petroni, F.; and Liang, P.

PEVLM: Parallel Encoding for Vision-Language Models F.; Lin, K.; Hewitt, J.; Paranjape, A.; Bevilacqua, M.; Petroni, F.; and Liang, P

Reference 17

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no resolver link, observed 2026-08-15T18:37:58.999389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:58.999389Z digest=sha256:503aba1b86787def7e04f1b070c8b42bf12491ae4032f0eb6fcb9f723886000f

Observation bfeb82a2-c625-43e6-9fdd-67ddfa07213b · outbound

This paper cites Robust Bayesian Method for Refutable Models.

PEVLM: Parallel Encoding for Vision-Language Models Robust Bayesian Method for Refutable Models

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:37:59.311242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.004156Z digest=sha256:7b233b0f06187749d6a0c7993ae2b8e2913fb3f64e20dd739da6d4da9a3d795c

Observation 893955ca-0f94-42ab-a852-13e4c8efe289 · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 19

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raw_fallback, observed 2026-08-15T18:37:59.592222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.009145Z digest=sha256:2f8d0f25c38b7bf497757ce0db57a043a77c44f7dc013645c393f16f29ebf214

Observation 3213bfb6-70c4-4b01-b1e7-eea06aa82be4 · outbound

This paper cites MoBA: Mixture of Block Attention for Long-Context LLMs.

PEVLM: Parallel Encoding for Vision-Language Models MoBA: Mixture of Block Attention for Long-Context LLMs

Reference 20

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no resolver link, observed 2026-08-15T18:37:59.014097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.014097Z digest=sha256:3de5f0b6f37af29b1494be071f7e55c81f02c1461bf8e3bef1228f5460a67d31

Observation 45fb3e26-c156-4315-aeb6-9a2fbf54690e · outbound

This paper cites TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text.

PEVLM: Parallel Encoding for Vision-Language Models TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text

Reference 21

Resolution
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no resolver link, observed 2026-08-15T18:37:59.019141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.019141Z digest=sha256:63e66acf6c5028085e34aaf412e5ff2c9962664566d28c758668cfe791af7fde

Observation 35115952-9044-4145-9578-9cd3f2533e56 · outbound

This paper cites Block-Attention for Efficient Prefilling.

PEVLM: Parallel Encoding for Vision-Language Models Block-Attention for Efficient Prefilling

Reference 22

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no resolver link, observed 2026-08-15T18:37:59.024047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.024047Z digest=sha256:23e564c4dd636f0ad69368df85e52724f39b539ec9f38ff5c68115587394a078

Observation 3d873379-3bd8-49cd-8044-ff41d72a6d91 · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.029882Z digest=sha256:dfc0df69fe2e857b240c8568760f15d3a8d31b6c1380f58732d5b23df6666e2b

Observation ba50c44e-d1c0-4608-9980-79f339380137 · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 24

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raw_fallback, observed 2026-08-15T18:37:59.564690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.035060Z digest=sha256:42e25c8ecc269fefd2ab99aa72d1005d71d8e8068e8c438f4293e89509207ff5

Observation 0377c4f0-b363-495e-a3cc-e7532079926b · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 25

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raw_fallback, observed 2026-08-15T18:37:59.549053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.039875Z digest=sha256:baec4f986ff72b3309e7ae634d07638342cc8bbf6bb5b6add1bfb46b448f35db

Observation 3ecb271d-02ec-4e57-b75e-48f7af9b5028 · outbound

This paper cites Parallel Context Windows for Large Language Models.

PEVLM: Parallel Encoding for Vision-Language Models Parallel Context Windows for Large Language Models

Reference 26

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no resolver link, observed 2026-08-15T18:37:59.044692Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.044692Z digest=sha256:47a70299f7e589fe183bf73b1670574938e2a09519cb2a38731b7f8d3059db04

Observation a8cfbe6d-2231-4c8b-8721-906e352e75b4 · outbound

This paper cites Massive Activations in Large Language Models.

PEVLM: Parallel Encoding for Vision-Language Models Massive Activations in Large Language Models

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.050314Z digest=sha256:4412220cc13c6cb49459d8e0851132a346f85f56604d9d89e8a6dbcf8c0eb67e

Observation d4a4adf9-5493-4135-9bd3-3bc2643f4b71 · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 28

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raw_fallback, observed 2026-08-15T18:37:59.531659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.055422Z digest=sha256:de5f8e0d37fd2b5dfe068a35c4977741630283be6f9758ea195d92f8a3ab93de

Observation e2f16849-d3b6-4f79-8f49-8025349f590a · outbound

This paper cites Softmax is not Enough (for Sharp Size Generalisation).

PEVLM: Parallel Encoding for Vision-Language Models Softmax is not Enough (for Sharp Size Generalisation)

Reference 29

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no resolver link, observed 2026-08-15T18:37:59.060322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.060322Z digest=sha256:3c40d8a6772b3d1ffc9fa3caac0406970e5880c1078080b696e570eee5d8c54f

Observation 9744f1cc-06a1-4d44-a00b-c8fcec72b221 · outbound

This paper cites Clifford algebra Cl(0,6) approach to beyond the standard model and naturalness problems.

PEVLM: Parallel Encoding for Vision-Language Models Clifford algebra Cl(0,6) approach to beyond the standard model and naturalness problems

Reference 30

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unresolved
no resolver link, observed 2026-08-15T18:37:59.065629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.065629Z digest=sha256:0e23a36db8c23ec88608baa4def23e943972d27b38070e7459bdeb757d3ec2d2

Observation 2275138c-f067-4a93-ae58-2c934f4befeb · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 31

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unresolved
raw_fallback, observed 2026-08-15T18:37:59.515058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.071345Z digest=sha256:fbb81b6266b564a5299ca24b40bbc566644563970fa6aa574f68adfc7c39538b

Observation 16baed7a-b570-45b1-b29e-a1c95c4b091c · outbound

This paper cites Long-Context Language Modeling with Parallel Context Encoding.

PEVLM: Parallel Encoding for Vision-Language Models Long-Context Language Modeling with Parallel Context Encoding

Reference 32

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no resolver link, observed 2026-08-15T18:37:59.076039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.076039Z digest=sha256:a5c47270cf714c9b9a0f357c34cd63a0e12158b5987ac68446d88e1679183e37

Observation ffeeaffb-9997-4dc8-ba12-06774c8b5f97 · outbound

This paper cites Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention.

PEVLM: Parallel Encoding for Vision-Language Models Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.081246Z digest=sha256:023462398dd012d8e713d80d376938acbe8f4fe38be85001e5c701e9bedffc10

Observation e07ddd8d-8e4e-428e-8703-371b9de17fae · outbound

This paper cites an unresolved cited work.

PEVLM: Parallel Encoding for Vision-Language Models Unresolved cited work

Reference 34

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raw_fallback, observed 2026-08-15T18:37:59.498764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T18:37:59.086042Z digest=sha256:db208d06c7e4d0bfcf5690374fa610a3a2b119b0a23928113af803924fb18069

Observation 5c6f9491-42ce-493a-9381-f9032109337c · outbound

This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.

PEVLM: Parallel Encoding for Vision-Language Models LLaVA-Video: Video Instruction Tuning With Synthetic Data

Reference 35

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no resolver link, observed 2026-08-15T18:37:59.090863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.090863Z digest=sha256:46028e42834a62a7f2909ed39fff23a68d16c85346f4cdef130854a5f48ef2f5

Observation 13235896-b8b4-4127-ae9a-178803805ee3 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

PEVLM: Parallel Encoding for Vision-Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:37:59.095922Z digest=sha256:d5f4bcc2f9a07763faf72320d0b329002560df244834f2bab00646207005eb6f

Pith citing papers

Observation 5489b355-2533-4bf1-916f-a55771522dbc · inbound

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation cites this paper.

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation PEVLM: Parallel Encoding for Vision-Language Models

Reference 103

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:05:57.992297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T16:17:09.834609Z digest=sha256:ca5f24c6ad30f9986253d9f32eccc4bb7b3a1bbf64e21be4e10cbf5f95a1dc47