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Paper Citation Record · LEDGER

CLGRPO: Reasoning Ability Enhancement for Small VLMs

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.18048.

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

pith.paper-citation-record.v1
2506.18048 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:27:46.110145Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 888e2e60-e219-475c-aaa1-b528e274bd99 · outbound

This paper cites Qwen2.5-VL Technical Report.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen2.5-VL Technical Report

Reference 1

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source=pdf_text observed=2026-08-06T23:27:45.974336Z digest=sha256:a50eab65fc65d518417697e47ee63e57687d18d83298cdfee0f348b9157869ef

Observation a1cba944-ef9a-4c3a-a1c9-8028410c4f07 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 2

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source=pdf_text observed=2026-08-06T23:27:45.979535Z digest=sha256:9d0faf8dd0689721c8718d2f7c42954eab947c24cd4ab762d5d4ad02a76eb5c5

Observation f2dd7f1e-2c03-4ef2-a355-09707d2a1102 · outbound

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

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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source=pdf_text observed=2026-08-06T23:27:45.983521Z digest=sha256:72b360d21dba9c92c14ac0edd4bc520ca1fefddc3269844f304098c526b6c116

Observation cba8af1b-81fd-4ced-9f49-ae5ffed51561 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

CLGRPO: Reasoning Ability Enhancement for Small VLMs InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 4

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source=pdf_text observed=2026-08-06T23:27:45.989262Z digest=sha256:bc055fdaf00166c62432b23d3ab9e47919fcde7680e8e9c28231efc756db664f

Observation 90a389ff-562d-4d1b-91ea-8c4c79769133 · outbound

This paper cites Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% performance,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% performance,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T23:27:46.470968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:45.994230Z digest=sha256:ab4c09bf8a58375ff788c2bb2cc4f747794ff9947db5aaa6ecbe92f27b9b76ce

Observation 6d3a24bb-b916-4c08-ab3f-7e6750106c24 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks,

Reference 6

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source=pdf_text observed=2026-08-06T23:27:45.999090Z digest=sha256:6360add30616adbe436d91e4440d2a157ca4108cdf59445de3c6f88674111b44

Observation 50e3175e-3585-44a1-98de-9522d7dd512d · outbound

This paper cites DeepSeek-V3 Technical Report.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeek-V3 Technical Report

Reference 7

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source=pdf_text observed=2026-08-06T23:27:46.003577Z digest=sha256:a93194872f94c1507a135896dfa2f07fb38cc97b9efc8832bd9861e7ca5395bb

Observation e0358bca-d770-4939-a258-2b3bc14b349a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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source=pdf_text observed=2026-08-06T23:27:46.007744Z digest=sha256:389fbf6ea499dc7c9076186265e2206ddcdc213d772a643a4019ade1ff2f538c

Observation 42dd53b1-eaeb-4e1d-b910-9944b3080290 · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 9

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source=pdf_text observed=2026-08-06T23:27:46.011940Z digest=sha256:9c73b4c1572a75ac8c9483992d554eb995799c2e8d6dcc169328c2996ab26555

Observation d0fb5213-c107-4e06-92fa-b3a58308bd0f · outbound

This paper cites Deepseek-vl: Towards real-world vision-language understanding,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Deepseek-vl: Towards real-world vision-language understanding,

Reference 10

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raw_fallback, observed 2026-08-06T23:27:46.453110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.016387Z digest=sha256:ce228d131a486bec03dc860e2b9ddfa2816d6a6956bd5db0f3405467672c0f70

Observation 5f0c31ce-2ba5-405e-8461-e7f9f6165736 · outbound

This paper cites Fastvlm: Efficient vision encoding for vision language models,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Fastvlm: Efficient vision encoding for vision language models,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.019994Z digest=sha256:f762af415ec36dafec2d3ec687474a973c6ba0fa2ced7c57f4f027b49d46fbae

Observation ed8b03db-ccc0-4a2b-9581-1552711e4495 · outbound

This paper cites Emoset: A large-scale visual emotion dataset with rich attributes,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Emoset: A large-scale visual emotion dataset with rich attributes,

Reference 12

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raw_fallback, observed 2026-08-06T23:27:46.431841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.023951Z digest=sha256:e4a2330f628c26be905f8a8a825c667986cbe877684d66b14b73c4637515d375

Observation ce9df91b-8665-4023-9d7b-f4c7c11313ee · outbound

This paper cites How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites,

Reference 13

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source=pdf_text observed=2026-08-06T23:27:46.027925Z digest=sha256:087e4ade92e9c3fcd0c3f6a1668c588369db7638d24ad5ed9a754bb3f7304d79

Observation 206915a0-b4c3-415f-a14c-faa7b1913a53 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 14

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source=pdf_text observed=2026-08-06T23:27:46.031851Z digest=sha256:2d1e9c4c7fd2f9a69ab431d63d9133ae65463f0604f5943c71a3546c54909132

Observation 5ed44390-3232-42df-8999-d4f09e64286c · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

CLGRPO: Reasoning Ability Enhancement for Small VLMs DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 15

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source=pdf_text observed=2026-08-06T23:27:46.035574Z digest=sha256:88febcee45db92e9bcd9f966eaefb0b141018caf07d1cad005b070a82e9dd76d

Observation e1df0161-d7f3-42f0-8aef-8431d30554c3 · outbound

This paper cites MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices.

CLGRPO: Reasoning Ability Enhancement for Small VLMs MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:46.040045Z digest=sha256:6ac5a9478ec2312b68ef9f8ae44209d36bbb78a7258984102ec2bdd14078fa62

Observation 89775a5f-8141-4c5f-9d31-b8158f2da8b5 · outbound

This paper cites Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization

Reference 17

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source=pdf_text observed=2026-08-06T23:27:46.044306Z digest=sha256:7f38b090251c2a085fe94355e75ba0499f5d3c32d13bf10069a614674e79948b

Observation c8760376-d25b-4280-92e6-05e754f0d73a · outbound

This paper cites Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput

Reference 18

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source=pdf_text observed=2026-08-06T23:27:46.048132Z digest=sha256:4a45ae78cee54815ab46df683631fc6cb18803a80eec40835f5999e9d0b58abb

Observation c480aeb5-07ba-42a7-8fbf-2accc3867fe6 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Direct preference optimization: Your language model is secretly a reward model,

Reference 20

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raw_fallback, observed 2026-08-06T23:27:46.414377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.055921Z digest=sha256:150a0f6d076d4c8cc7c6cbe0222068bd07a4889107853c3e0f679ceccf42640a

Observation d207f646-328b-46ae-86d1-f2c88e1be30d · outbound

This paper cites Bluelm: An open multilingual 7b language model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Bluelm: An open multilingual 7b language model,

Reference 21

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raw_fallback, observed 2026-08-06T23:27:46.401648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.065185Z digest=sha256:9ba721232c3d747711f2f081568c1ff64dbe8e001f4aaa57859a972fbc4a9631

Observation ceb4a625-f154-4dfd-a0d3-1f6ddc62b22b · outbound

This paper cites Qwen3 Technical Report.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Qwen3 Technical Report

Reference 22

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source=pdf_text observed=2026-08-06T23:27:46.069055Z digest=sha256:bd629347a041629a8acdcb088608e66d559bdbcd08caf2e23996a1dce9aaa39a

Observation de30002b-577a-4f35-9999-6e7832abf485 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 23

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source=pdf_text observed=2026-08-06T23:27:46.073417Z digest=sha256:0f6f7a12cb9f09ece62c6e37a81bb62a9685b02f86e04563acab1f13743ab672

Observation 3b9f84a9-5d91-40d6-9fce-e92fbd59d6e5 · outbound

This paper cites Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning,

Reference 24

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.077559Z digest=sha256:0333c0ebaa7ec68944f5c545297b5e243fd9b48af6ececd3b747ba66633870df

Observation 9bcb828f-6da3-46a2-ba53-51a42189d87b · outbound

This paper cites Cot-vla: Visual chain-of- thought reasoning for vision-language-action models,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Cot-vla: Visual chain-of- thought reasoning for vision-language-action models,

Reference 25

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raw_fallback, observed 2026-08-06T23:27:46.379161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.082144Z digest=sha256:788b0dbd437a339daff117d5dbbf86de110f73c01d3417d05854344fe80235c9

Observation ee782dab-a378-4cef-afb2-e68922e5d2a0 · outbound

This paper cites Proximal Policy Optimization Algorithms.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Proximal Policy Optimization Algorithms

Reference 26

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source=pdf_text observed=2026-08-06T23:27:46.086111Z digest=sha256:02afa03a5b7d81603f3649ad5600251782299f395c15fa33f660ff3742222894

Observation d977a308-3fa7-47c9-a607-864a0119acc8 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Direct preference optimization: Your language model is secretly a reward model,

Reference 27

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raw_fallback, observed 2026-08-06T23:27:46.368226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.090218Z digest=sha256:0ddb4482721cc5f0d0bcd5f36e762850f9eca513e778bf5aa9e2f996f8060b3c

Observation d4c51025-8c1d-4790-a00e-684a8a9963f4 · outbound

This paper cites Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms

Reference 28

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source=pdf_text observed=2026-08-06T23:27:46.094169Z digest=sha256:e518b727f169bef33cb3e83576bf7291d36738ea2595c79dc475dfb17a626fc8

Observation c14be14c-f2bb-49ec-8019-2b136d1f5c00 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Understanding R1-Zero-Like Training: A Critical Perspective

Reference 29

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source=pdf_text observed=2026-08-06T23:27:46.098401Z digest=sha256:da4ce166436d8ab3cd07e685cbf6e97fec52550cad59e72c72a9593cd8e683e8

Observation 3e0302b2-4c90-4d32-b153-02826c9f8c20 · outbound

This paper cites u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model.

CLGRPO: Reasoning Ability Enhancement for Small VLMs u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:46.102560Z digest=sha256:3c0e1139a17dcaaf5f845a7893bdc644c76263d9ac83cc71ea020d4a68fdb568

Observation 6fe2d866-1107-4922-acda-7c305a133f15 · outbound

This paper cites Reproducibility companion paper: u-llava: Unifying multi-modal tasks via large language model,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Reproducibility companion paper: u-llava: Unifying multi-modal tasks via large language model,

Reference 31

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raw_fallback, observed 2026-08-06T23:27:46.357321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.106556Z digest=sha256:593b62d45746191fe43ec460f14f133f6e9ffc57448944677136a78d1ed8d88b

Observation 83592d12-7e03-4866-aeeb-60cdca07b7c4 · outbound

This paper cites Overcoming heterogeneous data in federated medical vision-language pre-training: A triple-embedding model selector approach,.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Overcoming heterogeneous data in federated medical vision-language pre-training: A triple-embedding model selector approach,

Reference 32

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raw_fallback, observed 2026-08-06T23:27:46.344292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T23:27:46.110145Z digest=sha256:c29999e6b2dad9234f2c34413e14824e865a360bbc10766a3a3350a76b37fd53

Observation cdb15741-233e-411b-970c-9479855144e2 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

CLGRPO: Reasoning Ability Enhancement for Small VLMs Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 2023

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:46.060328Z digest=sha256:cc5a189a5a2d2c4360a8f45a01b3806ced5e29b53890fcfc6f8ce1d2d08a181a

Pith citing papers

No inbound Pith citation observations are available.