Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:01:49.976800Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 0 inbound Pith citation observations for arXiv:2506.20214.
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 2026-08-06T23:01:49.976800Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
Source: cited_works
94 of 94 outbound references displayed
External citation measurements
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Observation 872bb111-9d23-41b6-9b8e-0ae57d180100 · outbound
UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation GPT-4 Technical Report
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Reference 9
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Reference 11
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Mai: A multi-turn aggregation- iteration model for composed image retrieval
Reference 12
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Reference 13
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Observation a7fe78e5-91cf-4dcf-82af-54c450071935 · outbound
UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Semhitok: A unified image tokenizer via semantic-guided hierarchical codebook for multimodal understanding and generation.arXiv preprint arXiv:2503.06764, 2025
Reference 14
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation
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Reference 17
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Eva-02: A visual representation for neon genesis.Image and Vision Computing, 149:105171, 2024
Reference 18
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Reference 19
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Reference 21
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation A survey on self-supervised learning: Algorithms, applications, and future trends.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
Reference 22
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation A diagram is worth a dozen images
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Autoregressive image generation using residual quantization
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Observation 2208cd6b-3b7a-431b-924a-1ad2e4eedd7d · outbound
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Observation 69d9c7a3-63e9-4f07-b34c-8b154f8d7278 · outbound
UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Improved baselines with visual instruction tuning
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Observation 801b98e7-a0c7-4180-875f-475dbc187d5f · outbound
UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023
Reference 36
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Reference 47
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Sigmoid loss for language image pre-training
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Token dynamics: Towards efficient and dynamic video token representation for video large language models.arXiv preprint arXiv:2503.16980, 2025
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Unified multimodal understanding and generation models: Advances, challenges, and opportunities.arXiv preprint arXiv:2505.02567, 2025
Reference 83
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Addressing representation collapse in vector quantized models with one linear layer.arXiv preprint arXiv:2411.02038, 2024
Reference 88
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Let E={e 1, ...,eN } ⊂Rd denote visual embeddings sampled from a distribution p(e), and let C={c 1, ...,cK} ⊂Rd be a codebook with K discrete centroids
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UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation Let y be a semantic target label (e.g., object class, scene type), and let v=Q(e) be the discrete token assigned to embeddinge
Reference 92
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Reference 93
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