Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:51:16.116733Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2508.01236.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:51:16.116733Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
61 of 61 outbound references displayed
External citation measurements
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models GPT-4 Technical Report
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source Datasets
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Observation ee9b3ab0-eea4-4437-8ad0-ab141f816c50 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification
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Observation 82d6d2e8-d2be-4445-ad49-ddb79af545b8 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Pyramid-BERT: Reducing Complexity via Successive Core-set based Token Selection
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Observation 0ec91359-8c53-4e84-b69b-91de2c83e776 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension
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Observation b769fd6f-7add-47d9-b905-f31e3358104b · outbound
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models TokenPacker: Efficient Visual Projector for Multimodal LLM
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Observation 6ffbb7d5-a195-44fb-8963-eefc5b6d95c2 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
Reference 21
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Observation 8d4a8035-c364-4586-ba74-5874fe2d81fa · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference
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Observation 6b4561a5-51d9-4ff8-9b80-e6cc175cfede · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models DeepSeek-VL: Towards Real-World Vision-Language Understanding
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Observation 7252d8d3-4b03-4f67-9854-851219f8eb87 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
Reference 30
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
Reference 31
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models ClipCap: CLIP Prefix for Image Captioning
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Observation 71c55e8e-6582-427f-a339-8cc12302f202 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Spatial-Aware Efficient Projector for MLLMs via Multi-Layer Feature Aggregation
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Observation 4fd76f7e-3374-4bed-ad1f-820c3fb42bfe · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Observation e62aeaec-4fbe-4611-8b09-740906e6bb17 · outbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
Reference 38
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Aligning Large Multimodal Models with Factually Augmented RLHF
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models LLaMA: Open and Efficient Foundation Language Models
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Unresolved cited work
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Advances in neural information processing systems 35 (2022), 23716–23736
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Evaluating Object Hallucination in Large Vision-Language Models
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