Paper Citation Record · LEDGER

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

As of 13 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 8 inbound Pith citation observations for arXiv:2412.03704.

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

pith.paper-citation-record.v1
2412.03704 v3

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:18:01.740237Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

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measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:18:41.089878Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:24:40.386203Z

Reference resolution

75 of 75 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c8e51b86-0b81-4d14-805d-e682e575598f · outbound

This paper cites https://openai.com/ index/learning-to-reason-with-llms/ , 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension https://openai.com/ index/learning-to-reason-with-llms/ , 2024

Reference 1

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Observation 9a0e4367-0052-46e6-bb5f-fa2511edaac3 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Flamingo: a visual language model for few-shot learning

Reference 2

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Observation 7e85f58e-88a0-4cb7-ab22-cfc79e54d146 · outbound

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

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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This paper cites Improving image generation with better captions.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Improving image generation with better captions

Reference 4

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Observation 2c120969-fdb5-4970-893e-4efbcaca9674 · outbound

This paper cites Large Language Monkeys: Scaling Inference Compute with Repeated Sampling.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Reference 5

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Observation 06c1ee18-8307-4e8c-9f93-ada6a01830dc · outbound

This paper cites Transfer Q Star: Principled Decoding for LLM Alignment.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Transfer Q Star: Principled Decoding for LLM Alignment

Reference 6

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Observation 64a4b06c-2c93-4cdf-a64e-07dcfb3bd8ea · outbound

This paper cites Conceptual 12m: Pushing web-scale image-text pre- training to recognize long-tail visual concepts.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Conceptual 12m: Pushing web-scale image-text pre- training to recognize long-tail visual concepts

Reference 7

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Observation f8594860-4568-4fcd-98a5-7b1f76e26593 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 8

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This paper cites Are we on the right way for evaluating large vision-language models?, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Are we on the right way for evaluating large vision-language models?, 2024

Reference 9

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Observation afe682d7-db3e-4580-ab11-ef480f6352dc · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 10

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Observation 681c3297-6802-4805-b162-e95bff58f360 · outbound

This paper cites Mitigating hallucination in visual language models with visual supervi- sion, 2023.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mitigating hallucination in visual language models with visual supervi- sion, 2023

Reference 11

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

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 12

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This paper cites Training Verifiers to Solve Math Word Problems.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Training Verifiers to Solve Math Word Problems

Reference 13

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This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 14

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This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing

Reference 15

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This paper cites Hal- lusionbench: An advanced diagnostic suite for entangled language hallucination and visual illusion in large vision- language models, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Hal- lusionbench: An advanced diagnostic suite for entangled language hallucination and visual illusion in large vision- language models, 2024

Reference 16

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This paper cites Temporal difference learning for model predictive control, 2022.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Temporal difference learning for model predictive control, 2022

Reference 17

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This paper cites V- star: Training verifiers for self-taught reasoners, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension V- star: Training verifiers for self-taught reasoners, 2024

Reference 18

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Scaling up vision-language pre-training for image captioning

Reference 19

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This paper cites Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Reference 20

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This paper cites Mantis: Interleaved multi-image instruction tuning, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mantis: Interleaved multi-image instruction tuning, 2024

Reference 21

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This paper cites Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Reference 22

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Veclip: Improving clip training via visual-enriched captions

Reference 23

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This paper cites Mitigating object hal- lucinations in large vision-language models through visual contrastive decoding, 2023.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mitigating object hal- lucinations in large vision-language models through visual contrastive decoding, 2023

Reference 24

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Llava-onevision: Easy visual task transfer, 2024

Reference 25

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Multimodal foundation models: From specialists to general-purpose as- sistants

Reference 26

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This paper cites Common 7b language models already possess strong math capabilities,.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Common 7b language models already possess strong math capabilities,

Reference 27

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Llava-next-interleave: Tackling multi-image, video, and 3d in large multimodal models, 2024

Reference 28

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Let's Verify Step by Step

Reference 29

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Let’s verify step by step,

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 31

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Visual instruction tuning, 2023

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Visual Instruction Tuning

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mmbench: Is your multi-modal model an all-around player?, 2024

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mathvista: Evaluating mathemat- ical reasoning of foundation models in visual contexts

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Gpt-4v(ision) system card

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Learning Transferable Visual Models From Natural Language Supervision

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Object Hallucination in Image Captioning

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mastering the game of go with deep neural networks and tree search

Reference 40

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Scaling llm test-time compute optimally can be more effec- tive than scaling model parameters, 2024

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Aligning large multimodal models with factually augmented rlhf, 2023

Reference 43

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Learning to predict by the methods of temporal differences

Reference 44

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Gemini: A family of highly capable multimodal models, 2023

Reference 45

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Motion planning for au- tonomous driving: The state of the art and future per- spectives

Reference 46

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Cambrian-1: A fully open, vision-centric exploration of multimodal llms,

Reference 48

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Solving math word problems with process- and outcome-based feedback

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension LiteSearch: Efficacious Tree Search for LLM

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension GIT: A Generative Image-to-text Transformer for Vision and Language

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Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Evaluation and Analysis of Hallucination in Large Vision-Language Models

Reference 52

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Observation 730e666d-9e08-4508-8ac5-a044788a2e10 · outbound

This paper cites Amber: An llm-free multi- dimensional benchmark for mllms hallucination evaluation,.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Amber: An llm-free multi- dimensional benchmark for mllms hallucination evaluation,

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Observation 8f38ebf9-b39a-4cf5-adf4-6ba44d024104 · outbound

This paper cites Mitigating fine-grained hallucination by fine-tuning large vision-language models with caption rewrites, 2023.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mitigating fine-grained hallucination by fine-tuning large vision-language models with caption rewrites, 2023

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Observation ff318e63-3c8c-4698-a560-d3c7aeaee043 · outbound

This paper cites Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution, 2024

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.915119Z

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Observation aedc8502-7c1c-4ad4-95b7-891a54621db9 · outbound

This paper cites an unresolved cited work.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Unresolved cited work

Reference 56

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Observation 39a38205-86a0-41d5-8e18-fbdee6d4621a · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension CogVLM: Visual Expert for Pretrained Language Models

Reference 57

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This paper cites COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL

Reference 58

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Observation 9771fe61-2df7-4e0a-b422-aa1e4f6af4bd · outbound

This paper cites Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement

Reference 59

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This paper cites Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning

Reference 60

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Observation ff63e70b-fe00-422a-bcd4-db3f26cf74c7 · outbound

This paper cites Mementos: A comprehensive benchmark for multimodal large language model reasoning over image se- quences.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mementos: A comprehensive benchmark for multimodal large language model reasoning over image se- quences

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.869239Z

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Observation e285b9f4-bcea-4119-a20d-f12ef37270f7 · outbound

This paper cites Simvlm: Simple visual language model pretraining with weak supervision.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Simvlm: Simple visual language model pretraining with weak supervision

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.844118Z

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Observation c5a6e8a7-8e28-4820-a95c-b7590ce2bde8 · outbound

This paper cites LoTLIP: Improving Language-Image Pre-training for Long Text Understanding.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension LoTLIP: Improving Language-Image Pre-training for Long Text Understanding

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T22:18:01.684754Z

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Observation 1fdfb2ca-fddb-4747-b46a-c96efeb225c0 · outbound

This paper cites GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment

Reference 64

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Observation 0f563b2d-9a8f-4bb2-8887-07245d840361 · outbound

This paper cites Longvila: Scaling long-context visual language models for long videos, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Longvila: Scaling long-context visual language models for long videos, 2024

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.822041Z

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Observation 1aad679e-8437-4ac3-9025-5d4fd14683ac · outbound

This paper cites Qwen2.5- math technical report: Toward mathematical expert model via self-improvement, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Qwen2.5- math technical report: Toward mathematical expert model via self-improvement, 2024

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.783235Z

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Observation 8f567c19-0bf3-4de4-a897-560cf547d4fc · outbound

This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T22:18:01.703890Z

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Observation e1d3a0bc-a400-4c88-8adb-7e38673599d7 · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T22:18:01.708355Z

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Observation 106b08e4-2f6a-4260-a435-e521e6c9bc62 · outbound

This paper cites Mm-vet: Evaluating large multimodal models for integrated capabilities, 2023.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mm-vet: Evaluating large multimodal models for integrated capabilities, 2023

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.751846Z

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Observation 4fc5ca45-ac36-4aae-8c54-a660053d2101 · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Florence: A New Foundation Model for Computer Vision

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T22:18:01.717840Z

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Observation 408aa513-503c-46bb-ba62-0f3c7b5a7bf8 · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understand- ing and reasoning benchmark for expert agi, 2024.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Mmmu: A massive multi-discipline multimodal understand- ing and reasoning benchmark for expert agi, 2024

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.731493Z

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Observation 6b01f65d-f688-4e31-b814-775cf5a28ef1 · outbound

This paper cites ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

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Resolution: unresolved; no resolver link, observed 2026-08-11T22:18:01.727434Z

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Observation dd2b288a-b1a9-4041-845f-76fcceae8dc8 · outbound

This paper cites Beyond hallucinations: Enhanc- ing lvlms through hallucination-aware direct preference op- timization, 2023.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Beyond hallucinations: Enhanc- ing lvlms through hallucination-aware direct preference op- timization, 2023

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:18:02.710461Z

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Observation 13aee097-c0bf-44e9-93b6-0c71c731b307 · outbound

This paper cites Aligning Modalities in Vision Large Language Models via Preference Fine-tuning.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

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Observation 20b19f1c-6d04-4809-b93b-f02199b97e12 · outbound

This paper cites Calibrated Self-Rewarding Vision Language Models.

Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension Calibrated Self-Rewarding Vision Language Models

Reference 75

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Pith citing papers

Observation e1cacfed-d5a6-4c9a-857a-9f80a2ba00dc · inbound

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InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 96

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Observation d5603a6b-9393-46dd-8c6e-5c5d0a5c7a09 · inbound

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Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 55

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Observation b69cd9cc-54b3-45bf-9283-819838cacd21 · inbound

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Point-RFT: Improving Multimodal Reasoning with Visually Grounded Reinforcement Finetuning Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 33

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Observation 246c9b34-c7f0-4ca4-bee2-4043cdf08d90 · inbound

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Mitigating Object Hallucination via Robust Local Perception Search Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 36

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Observation b54b5691-eafa-49dc-87b5-550f54f6c437 · inbound

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What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:18.661384Z

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Observation d0da67b2-01d5-4d05-a158-b71c70f17dfa · inbound

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ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 60

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Observation 6add957d-08f8-48a0-9bdf-d3f310ccc30a · inbound

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Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T23:57:22.096140Z

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Observation e74bdea1-5859-4b61-a8b2-633f4646b1b9 · inbound

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LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension

Reference 50

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