Paper Citation Record · LEDGER

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding

As of 14 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2501.10967.

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

pith.paper-citation-record.v1
2501.10967 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:53:21.337583Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:33:53.715127Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:33:59.190592Z

Reference resolution

58 of 58 outbound references displayed

verified exact1
verified fuzzy0
unresolved57
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd728695-fe16-4c4e-93bc-57d78dbf47a0 · outbound

This paper cites URL: " 'urlintro :=.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding URL: " 'urlintro :=

Reference 1

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Source-reported events for the cited work

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Observation 1e1ed59a-42e7-4036-a0a8-c8cae395c280 · outbound

This paper cites write newline.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding write newline

Reference 2

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Source-reported events for the cited work

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Observation 5786a460-1c18-437c-ae02-9830bba80b54 · outbound

This paper cites GPT-4 Technical Report.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding GPT-4 Technical Report

Reference 3

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Observation 3f1e3c33-a0b7-4528-93c8-83bc459fe542 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 4

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Observation 65ca5de0-af9b-4ccd-bfa6-d8ecacc75b25 · outbound

This paper cites an unresolved cited work.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 5

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Source-reported events for the cited work

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Observation 51e49b39-3cea-45e4-9068-3b340d657146 · outbound

This paper cites an unresolved cited work.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 6

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Source-reported events for the cited work

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Observation 51464a4a-ffcf-4210-9e2f-cfb33c83271f · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 7

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Source-reported events for the cited work

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Observation 1b14393b-8007-46ad-8a5f-cb8277c9670f · outbound

This paper cites LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing

Reference 8

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Observation b3880363-f873-48c8-98a8-aff26caa6c42 · outbound

This paper cites MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 9

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Source-reported events for the cited work

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Observation daf33d11-56da-4485-8da8-ded14d604195 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad34788c-ce41-4ede-95a2-2043812b615f · outbound

This paper cites VisionLLaMA: A Unified LLaMA Backbone for Vision Tasks.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding VisionLLaMA: A Unified LLaMA Backbone for Vision Tasks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T18:53:21.155051Z

Source-reported events for the cited work

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Observation 0a3d22f0-2778-4a2d-b7fd-3ff154b867d7 · outbound

This paper cites Conditional Positional Encodings for Vision Transformers.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Conditional Positional Encodings for Vision Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T18:53:21.160206Z

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Observation 62e118f4-ef7a-4979-9a29-dcbec9eedb22 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T18:53:21.163914Z

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Observation fe7a0637-b79c-455d-8e71-86b8aa567b47 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 14

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This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 15

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Observation 4bb4cd20-1813-4b85-9ac8-ff9322f3d676 · outbound

This paper cites an unresolved cited work.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 16

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Observation 9533b3e9-3db5-4cba-92e3-c9ed8fe00f30 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 17

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Observation 72d86c38-aa0b-43ab-840e-59b631c2b669 · outbound

This paper cites an unresolved cited work.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 18

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Source-reported events for the cited work

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Observation ba211248-19a1-49d9-b6d6-02649e595073 · outbound

This paper cites an unresolved cited work.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 19

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Observation 0f1687e1-d1c9-4d6f-bf6e-eafa10da89d8 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 20

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Observation c9a6236e-7d34-4ff6-944a-789e22ec86c2 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding How Much Position Information Do Convolutional Neural Networks Encode?

Reference 21

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 22

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Observation 98ca37df-6dc3-4f06-81a4-12e2a5c9b12a · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 23

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Observation c79ad036-6786-49a8-964c-c40a3f80f969 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

Reference 24

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Observation eb81aa44-c08f-4884-9f02-50748bdcd999 · outbound

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 25

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Evaluating Object Hallucination in Large Vision-Language Models

Reference 26

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Textbooks Are All You Need II: phi-1.5 technical report

Reference 27

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding FiT: Flexible Vision Transformer for Diffusion Model

Reference 33

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Kosmos-2: Grounding Multimodal Large Language Models to the World

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Self-Attention with Relative Position Representations

Reference 39

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Llama 2: Open Foundation and Fine-Tuned Chat Models

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Mitigating Object Hallucination via Concentric Causal Attention

Reference 50

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

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Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 56

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Observation 8d05c34b-f13f-4580-8ad8-275f0d5552ff · outbound

This paper cites an unresolved cited work.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding Unresolved cited work

Reference 57

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This paper cites TinyLLaVA: A Framework of Small-scale Large Multimodal Models.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding TinyLLaVA: A Framework of Small-scale Large Multimodal Models

Reference 58

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Observation 22035ef3-ee65-4c95-a16f-ec251a2eaf41 · inbound

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models cites this paper.

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding

Reference 9

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