Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T10:49:52.282672Z
Paper Citation Record · LEDGER
PruneVid: Visual Token Pruning for Efficient Video Large Language Models
As of 14 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 11 inbound Pith citation observations for arXiv:2412.16117.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:11:49.166898Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T19:16:31.884188Z
Reference resolution
42 of 42 outbound references displayed
- verified exact0
- verified fuzzy32
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a8ed0265-8631-425c-94c2-ad34909d2cde · outbound
This paper cites write newline.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models write newline
Reference 1
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30473d58-f116-4053-bd1a-05e46582f1a3 · outbound
This paper cites Gpt-4 technical report.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Gpt-4 technical report
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.926719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 24cf1b02-3b0c-4215-83c3-b0644fce1bb7 · outbound
This paper cites Token merging: Your vit but faster.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Token merging: Your vit but faster
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.910981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d9f85c15-d746-46a3-9c7a-7fa9c099bb4a · outbound
This paper cites An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.894952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 9b5385b5-af5a-4a49-a855-7686442ec1f5 · outbound
This paper cites Study on density peaks clustering based on k-nearest neighbors and principal component analysis.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Study on density peaks clustering based on k-nearest neighbors and principal component analysis
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.878958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 88ec6223-67ae-4794-8672-c06896802dce · outbound
This paper cites Slowfast networks for video recognition.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Slowfast networks for video recognition
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.106189Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80bb6965-da4c-4a9e-bcc2-b4610da4b881 · outbound
This paper cites Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.852860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d3366fe1-9738-43b6-bced-577444a029bd · outbound
This paper cites Visual hallucinations of multi-modal large language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Visual hallucinations of multi-modal large language models
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.836547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 09420e7a-1b5e-45ac-89f0-207dcf335507 · outbound
This paper cites Chat-univi: Unified visual representation empowers large language models with image and video understanding.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Chat-univi: Unified visual representation empowers large language models with image and video understanding
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.121305Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 362e2a01-8708-4b6e-8e27-43cf5acbc5a9 · outbound
This paper cites An image grid can be worth a video: Zero-shot video question answering using a vlm.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models An image grid can be worth a video: Zero-shot video question answering using a vlm
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.809348Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f7a02555-cc91-4288-892d-9518d6300505 · outbound
This paper cites Spvit: Enabling faster vision transformers via latency-aware soft token pruning.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Spvit: Enabling faster vision transformers via latency-aware soft token pruning
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.793398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 7366d366-22a8-42ed-b489-fff6b0b1a64c · outbound
This paper cites LLaVA-OneVision: Easy Visual Task Transfer.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models LLaVA-OneVision: Easy Visual Task Transfer
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.135759Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bfda57c7-00f7-48a7-b788-59aab23c68da · outbound
This paper cites Videochat: Chat-centric video understanding.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Videochat: Chat-centric video understanding
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.777893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 53e4dbbc-d041-417c-8a3f-fcd9abeda59b · outbound
This paper cites Unmasked teacher: Towards training-efficient video foundation models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Unmasked teacher: Towards training-efficient video foundation models
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.762358Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d4ac5416-df6d-4fd7-a6b0-bcab107d6709 · outbound
This paper cites Mvbench: A comprehensive multi-modal video understanding benchmark.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Mvbench: A comprehensive multi-modal video understanding benchmark
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.150713Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 66e32273-bb97-4973-9e37-847d0845211b · outbound
This paper cites Llama-vid: An image is worth 2 tokens in large language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Llama-vid: An image is worth 2 tokens in large language models
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.735877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 88a193d4-94dc-420d-8cad-ec0a1bf467aa · outbound
This paper cites Video-llava: Learning united visual representation by alignment before projection.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Video-llava: Learning united visual representation by alignment before projection
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.720410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 01479777-00bf-465c-8921-da0de4ad68d5 · outbound
This paper cites Vila: On pre-training for visual language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Vila: On pre-training for visual language models
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.704059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3d365085-e043-45d3-81b4-72357ab214bc · outbound
This paper cites Visual instruction tuning.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Visual instruction tuning
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.687922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c1dfc92f-58b0-4cad-acd9-d52448e12134 · outbound
This paper cites St-llm: Large language models are effective temporal learners.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models St-llm: Large language models are effective temporal learners
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.670456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 444af41f-3654-4986-b6ad-dc803d627f54 · outbound
This paper cites Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.654884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 7fdf3f4f-fb51-4c9a-8f97-5b040ac77ae1 · outbound
This paper cites Efficient inference of vision instruction-following models with elastic cache.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Efficient inference of vision instruction-following models with elastic cache
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.637596Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b3513bb3-1bba-4acf-bc75-9b61ca1dfdcf · outbound
This paper cites Video-chatgpt: Towards detailed video understanding via large vision and language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Video-chatgpt: Towards detailed video understanding via large vision and language models
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.620788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d64665fc-a78a-4d1d-a015-e1d779b05a8d · outbound
This paper cites Egoschema: A diagnostic benchmark for very long-form video language understanding.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Egoschema: A diagnostic benchmark for very long-form video language understanding
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.604400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 655f4a8a-6c93-4915-94a0-32464f0e6001 · outbound
This paper cites Learning transferable visual models from natural language supervision.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Learning transferable visual models from natural language supervision
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.197356Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 88aee4a6-83c0-421f-bfdc-420889855522 · outbound
This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Dynamicvit: Efficient vision transformers with dynamic token sparsification
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.578089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a8e3060c-1a14-422b-a9f8-33fec2064078 · outbound
This paper cites Llava-prumerge: Adaptive token reduction for efficient large multimodal models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Llava-prumerge: Adaptive token reduction for efficient large multimodal models
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.562640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ed3450b3-cc7c-4344-87f6-d367817562d2 · outbound
This paper cites Llama: Open and efficient foundation language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Llama: Open and efficient foundation language models
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.546298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b6eb80ef-3fc5-4d0b-a3d0-31a93a4dcb93 · outbound
This paper cites Fastvit: A fast hybrid vision transformer using structural reparameterization.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Fastvit: A fast hybrid vision transformer using structural reparameterization
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.530444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 5427a9af-9822-40b5-8e07-c113af179731 · outbound
This paper cites Look-m: Look-once optimization in kv cache for efficient multimodal long-context inference.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Look-m: Look-once optimization in kv cache for efficient multimodal long-context inference
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.513566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b16479fe-e55b-4b5a-af37-f9777b044479 · outbound
This paper cites Tarsier: Recipes for training and evaluating large video description models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Tarsier: Recipes for training and evaluating large video description models
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.497397Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cf22f3e6-e6de-4dcb-8634-df72158be49a · outbound
This paper cites Actionclip: A new paradigm for video action recognition.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Actionclip: A new paradigm for video action recognition
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.481738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 8a6da8fc-f78e-4745-a4da-4d737627cc13 · outbound
This paper cites Internvideo2: Scaling video foundation models for multimodal video understanding.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Internvideo2: Scaling video foundation models for multimodal video understanding
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.465594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c16655bd-aa13-4471-99a6-9f99870feabb · outbound
This paper cites Freeva: Offline mllm as training-free video assistant.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Freeva: Offline mllm as training-free video assistant
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.448060Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 31e1dacb-9f1a-46bd-8f4b-ecb579dbbf47 · outbound
This paper cites Pllava: Parameter-free llava extension from images to videos for video dense captioning.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Pllava: Parameter-free llava extension from images to videos for video dense captioning
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.432007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b2381bee-dfb4-4b3d-bbe3-d858b3a27169 · outbound
This paper cites Slowfast-llava: A strong training-free baseline for video large language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Slowfast-llava: A strong training-free baseline for video large language models
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.415047Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b5078aeb-6a01-4692-9ec9-08b0ff3b3258 · outbound
This paper cites Qwen2 technical report.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Qwen2 technical report
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.398911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 3dbe2622-126b-46c3-adc4-dd4a1693e392 · outbound
This paper cites Video-llama: An instruction-tuned audio-visual language model for video understanding.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Video-llama: An instruction-tuned audio-visual language model for video understanding
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T10:49:52.380924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6d371b21-56f9-475d-bedf-703558c711fc · outbound
This paper cites H2o: Heavy-hitter oracle for efficient generative inference of large language models.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models H2o: Heavy-hitter oracle for efficient generative inference of large language models
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.265871Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac1d57e7-0fd6-4e11-b1b8-66fc4376ca5e · outbound
This paper cites @esa (Ref.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models @esa (Ref
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.270808Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77aa930a-754e-4b4d-8eee-8428bbef4323 · outbound
This paper cites an unresolved cited work.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Unresolved cited work
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.277452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8357fddf-4eb3-483c-8862-0e1b702a7478 · outbound
This paper cites an unresolved cited work.
PruneVid: Visual Token Pruning for Efficient Video Large Language Models Unresolved cited work
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:49:52.282672Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation d1096a89-6bc4-4e70-b5cf-9ab2e5fed281 · inbound
LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs cites this paper.
LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:24:27.055696Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d544c777-c601-45fb-a23e-d49639e58b38 · inbound
Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs cites this paper.
Multi-Granular Spatio-Temporal Token Merging for Training-Free Acceleration of Video LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:32:46.995554Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f29c4805-84c0-4a34-92c7-6508dc49d3ec · inbound
MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs cites this paper.
MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:41:15.535604Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 747571fc-405e-4119-b757-877208d82e2e · inbound
TrajTok: Learning Trajectory Tokens enables better Video Understanding cites this paper.
TrajTok: Learning Trajectory Tokens enables better Video Understanding PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:16:31.888882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 59c2e359-e839-46af-bc6a-e64c09bff64c · inbound
TrajTok: Learning Trajectory Tokens enables better Video Understanding cites this paper.
TrajTok: Learning Trajectory Tokens enables better Video Understanding PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T20:38:38.325046Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 352f6555-5169-49e5-ab23-c28f34d52a3b · inbound
Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models cites this paper.
Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T18:26:26.984952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation bf580084-5077-475c-b446-9c4c0ed3c70b · inbound
POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs cites this paper.
POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T10:41:03.942336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 391ab039-e668-49f0-92e4-cdc6a8d5e4a1 · inbound
Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation cites this paper.
Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 8
- Resolution
- unresolved
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Observation 6037976b-5fc2-4d7c-a168-9c15f12ab2bd · inbound
CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models cites this paper.
CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 10
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Observation c93e8ec9-6253-41fa-a4c4-35e752a53ea7 · inbound
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs cites this paper.
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 97
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Observation d9ce454e-6fdf-4a22-84c6-d681f1f16dce · inbound
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs cites this paper.
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs PruneVid: Visual Token Pruning for Efficient Video Large Language Models
Reference 97
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- no resolver link, observed 2026-08-07T00:11:49.166898Z
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