Paper Citation Record · LEDGER

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks

As of 21 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2505.12884.

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

pith.paper-citation-record.v1
2505.12884 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:29:00.857489Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T06:21:57.229717Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T08:06:48.286226Z

Reference resolution

53 of 53 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 17423ce2-1c98-46ea-bc8e-c625dc1f694d · outbound

This paper cites VQA: Visual Question Answering.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks VQA: Visual Question Answering

Reference 1

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Observation 8d0877ac-da7a-43fa-98de-8d171c4f7b55 · outbound

This paper cites Qwen2.5-vl technical report,.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Qwen2.5-vl technical report,

Reference 2

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Observation bcfed123-2fa0-4f4e-bbd7-6477c3840119 · outbound

This paper cites Wiki-LLaVA: Hierarchical Retrieval-Augmented Generation for Multimodal LLMs.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Wiki-LLaVA: Hierarchical Retrieval-Augmented Generation for Multimodal LLMs

Reference 3

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Observation d9fa5af5-c52d-480a-8a9d-e0567dd8aef1 · outbound

This paper cites MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 4

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Observation c997b720-00aa-4e76-9925-05d62ceae7a3 · outbound

This paper cites MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text

Reference 5

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Observation db5099d1-eb24-4893-9da6-e7a368e8a19f · outbound

This paper cites PaLI-X: On Scaling up a Multilingual Vision and Language Model.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks PaLI-X: On Scaling up a Multilingual Vision and Language Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:29:00.649803Z

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Observation f06f3a30-c59a-47f0-8b96-75633590212f · outbound

This paper cites InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Reference 7

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Observation a037dd18-e019-4312-93dd-6f16cbe51263 · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Gonzalez, Ion Stoica, and Eric P

Reference 8

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Observation 17d0cfc0-9276-4d20-a138-1a11debebd1f · outbound

This paper cites Mobilevlm : A fast, strong and open vision language assistant for mobile devices, 2023.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Mobilevlm : A fast, strong and open vision language assistant for mobile devices, 2023

Reference 9

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Observation 101b1fda-e4a3-45f6-830c-d9d6c6e6a498 · outbound

This paper cites MobileVLM V2: Faster and Stronger Baseline for Vision Language Model.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

Reference 10

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Observation 3caa645b-1b7b-4081-bfb4-d1166f4f2118 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 11

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Observation 414db313-0a32-49d8-a669-26395d368f6f · outbound

This paper cites Gemini 2.5 pro.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Gemini 2.5 pro

Reference 12

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Observation d6a7ea5e-b73f-4d0f-a3fc-efdfc9442a08 · outbound

This paper cites Textbooks Are All You Need.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Textbooks Are All You Need

Reference 13

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This paper cites REALM: Retrieval-Augmented Language Model Pre-Training.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks REALM: Retrieval-Augmented Language Model Pre-Training

Reference 14

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Observation 8f8585da-60de-4eda-ba67-4194516204cc · outbound

This paper cites REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory

Reference 15

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Observation 99d990e4-5bd0-415d-8b23-e28e0f3b4ca3 · outbound

This paper cites GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering

Reference 16

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This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 17

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Observation f9cf1c9b-9f00-4669-b44e-663f1c5293ec · outbound

This paper cites Shamma, Michael S.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Shamma, Michael S

Reference 18

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Observation 853b2d3a-5d30-45ca-8faf-b93b928485f0 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 19

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 20

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This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Evaluating Object Hallucination in Large Vision-Language Models

Reference 21

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This paper cites Microsoft COCO: Common Objects in Context.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Microsoft COCO: Common Objects in Context

Reference 22

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Visual Instruction Tuning

Reference 23

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Point- wise mutual information as a performance gauge for retrieval-augmented generation, 2025

Reference 24

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This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 25

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This paper cites Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

Reference 26

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks SmolVLM: Redefining small and efficient multimodal models

Reference 27

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Ocr-vqa: Visual question answering by reading text in images

Reference 28

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Gpt-4v(ision)

Reference 29

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Learning Transferable Visual Models From Natural Language Supervision

Reference 30

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks RAVEN: Multitask Retrieval Augmented Vision-Language Learning

Reference 31

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Towards VQA Models That Can Read

Reference 32

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks PaliGemma 2: A Family of Versatile VLMs for Transfer

Reference 33

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Gemma 2: Improving Open Language Models at a Practical Size

Reference 34

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive Pruning

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Qwen2 Technical Report

Reference 36

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 37

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MiniCPM-V: A GPT-4V Level MLLM on Your Phone

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Mm-vet: Evaluating large multimodal models for integrated capabilities,

Reference 40

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks TinyGPT-V: Efficient Multimodal Large Language Model via Small Backbones

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Sigmoid Loss for Language Image Pre-Training

Reference 43

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks TinyLlama: An Open-Source Small Language Model

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks TinyLLaVA: A Framework of Small-scale Large Multimodal Models

Reference 45

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 46

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks An information bottleneck perspective for effective noise filtering on retrieval-augmented generation, 2024

Reference 47

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks These represent visual information conditioned for the language model

Reference 51

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks This 2D representation facilitates direct scatter plot visualization

Reference 52

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks collapse

Reference 53

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

Reference 2016

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TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 2024

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b19ecd5e-7791-4e40-abc4-6c62ef150b4f · outbound

This paper cites Qwen2.5-VL Technical Report.

TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks Qwen2.5-VL Technical Report

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T20:29:00.630220Z

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Pith citing papers

Observation 91f75623-e115-441a-a03a-7c14efbec075 · inbound

State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading cites this paper.

State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:16:26.486082Z

Source-reported events for the cited work

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Observation 399f5aae-6630-4ac6-8a9d-6f7ef1c7b06b · inbound

MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models cites this paper.

MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models TinyAlign: Boosting Lightweight Vision-Language Models by Mitigating Modal Alignment Bottlenecks

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:06:48.287812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.