Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought | Paper Citation Record

Observation a72b6a48-f8a9-4501-a2b2-7024d85d6d1e · outbound

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

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

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This paper cites Qwen2.5-VL Technical Report.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Qwen2.5-VL Technical Report

Reference 2

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Graph of thoughts: Solving elab- orate problems with large language models

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This paper cites COYO-700M: Image-text pair dataset.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought COYO-700M: Image-text pair dataset

Reference 4

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This paper cites Image- level or object-level? A tale of two resampling strategies for long-tailed detection.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Image- level or object-level? A tale of two resampling strategies for long-tailed detection

Reference 5

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This paper cites Contrastive Localized Language-Image Pre-Training.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Contrastive Localized Language-Image Pre-Training

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

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 7

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This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

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Observation 3c50ad31-5af2-49ce-873c-eb9d295a5e35 · outbound

This paper cites ShareGPT4v: Improving large multi-modal models with better captions.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought ShareGPT4v: Improving large multi-modal models with better captions

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Unresolved cited work

Reference 10

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Observation 59c73fe4-db18-43d4-abc6-fa74c5e38fe5 · outbound

This paper cites UNITER: Universal image-text representation learning.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought UNITER: Universal image-text representation learning

Reference 11

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Observation 1f6b802d-337e-4a18-94f6-af9cec44b46a · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 12

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Observation 956ba49b-7030-4de3-b51f-e8d1562315f1 · outbound

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

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought InternVL: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 13

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

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Gonzalez, Ion Stoica, and Eric P

Reference 14

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This paper cites Control of goal- directed and stimulus-driven attention in the brain.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Control of goal- directed and stimulus-driven attention in the brain

Reference 15

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This paper cites TransVG: End-to-end visual grounding with transformers.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought TransVG: End-to-end visual grounding with transformers

Reference 16

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This paper cites An im- age is worth 16x16 words: Transformers for image recog- nition at scale.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought An im- age is worth 16x16 words: Transformers for image recog- nition at scale

Reference 17

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This paper cites EV A: Exploring the limits of masked visual represen- tation learning at scale.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought EV A: Exploring the limits of masked visual represen- tation learning at scale

Reference 18

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Observation 7c022133-ab69-429a-8f09-0e77fde0f459 · outbound

This paper cites EV A-02: A visual representa- tion for neon genesis.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought EV A-02: A visual representa- tion for neon genesis

Reference 19

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This paper cites Large-scale adversarial training for vision-and-language representation learning.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Large-scale adversarial training for vision-and-language representation learning

Reference 20

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This paper cites G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model

Reference 21

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This paper cites Mini-InternVL: a flexible-transfer pocket multi-modal model with 5% parameters and 90% perfor- mance.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Mini-InternVL: a flexible-transfer pocket multi-modal model with 5% parameters and 90% perfor- mance

Reference 22

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This paper cites Chain of Thought Prompt Tuning in Vision Language Models.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Chain of Thought Prompt Tuning in Vision Language Models

Reference 23

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Observation 7cbf3642-e9bd-4ae4-acc9-f3748b916f3f · outbound

This paper cites ICDAR2019 competition on scanned receipt ocr and information extrac- tion.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought ICDAR2019 competition on scanned receipt ocr and information extrac- tion

Reference 24

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This paper cites GQA: A new dataset for real-world visual reasoning and compositional question answering.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought GQA: A new dataset for real-world visual reasoning and compositional question answering

Reference 25

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This paper cites Psychology, briefer course.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Psychology, briefer course

Reference 26

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought DVQA: Understanding data visualizations via ques- tion answering

Reference 27

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought MDETR- modulated detection for end-to-end multi-modal under- standing

Reference 28

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Decoupling Representation and Classifier for Long-Tailed Recognition

Reference 29

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This paper cites Directed attention as a common resource for executive functioning and self- regulation.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Directed attention as a common resource for executive functioning and self- regulation

Reference 30

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This paper cites Referitgame: Referring to objects in pho- tographs of natural scenes.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Referitgame: Referring to objects in pho- tographs of natural scenes

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought A diagram is worth a dozen images

Reference 32

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Ocr- free document understanding transformer

Reference 33

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Segment Anything

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Berg, Wan-Yen Lo, Piotr Doll´ar, and Ross Girshick

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Large language models are zero-shot reasoners

Reference 36

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Shamma, Michael S

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought LLaVA-OneVision: Easy Visual Task Transfer

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Blip: Bootstrapping language-image pre-training for uni- fied vision-language understanding and generation

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought VoCoT: Unleashing Visually Grounded Multi-Step Reasoning in Large Multi-Modal Models

Reference 42

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought VILA: On pre-training for visual language models

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Microsoft COCO: Common objects in context

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Visual spa- tial reasoning

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Visual instruction tuning

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought LLaV A-NeXT: Im- proved reasoning, OCR, and world knowledge, 2024

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Grounding DINO: Mar- rying dino with grounded pre-training for open-set object detection

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought A convnet for the 2020s

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Decoupled Weight Decay Regularization

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This paper cites Learn to explain: Multimodal reason- ing via thought chains for science question answering.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Learn to explain: Multimodal reason- ing via thought chains for science question answering

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought ChartQA: A benchmark for question answering about charts with visual and logical reasoning

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This paper cites Docvqa: A dataset for vqa on document images.

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Docvqa: A dataset for vqa on document images

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Infographicvqa

Reference 57

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 58

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Architecture of connectivity within a cingulo- fronto-parietal neurocognitive network for directed atten- tion

Reference 59

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Brain mechanisms for directed at- tention

Reference 60

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Visual-O1: Understanding Ambiguous Instructions via Multi-modal Multi-turn Chain-of-thoughts Reasoning

Reference 61

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Observation b35e0369-055f-4f67-8cfb-a770b12e8cf8 · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Unresolved cited work

Reference 62

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 63

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models

Reference 64

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Learning transferable visual models from natural language supervision

Reference 65

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought GLaMM: Pixel grounding large multimodal model

Reference 66

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection

Reference 67

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Grounded sam: Assembling open-world models for diverse visual tasks,

Reference 68

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings

Reference 69

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Vi- sual CoT: advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning

Reference 70

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Objects365: A large-scale, high-quality dataset for object detection

Reference 71

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Observation 554fe99f-b054-4dac-98e2-9f52f98d8e3d · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Eagle: Explor- ing the design space for multimodal llms with mixture of encoders

Reference 72

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Textcaps: a dataset for image caption- ing with reading comprehension

Reference 73

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Towards VQA models that can read

Reference 74

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Introducing the next generation of claude,

Reference 75

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 76

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Emu3: Next-Token Prediction is All You Need

Reference 77

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Gemini: A Family of Highly Capable Multimodal Models

Reference 78

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 79

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Laion-gpt4v dataset, 2023

Reference 80

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought The Llama 3 Herd of Models

Reference 81

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought GPT-4 Technical Report

Reference 82

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought InternVL2: Better than the best—expanding performance boundaries of open-source multimodal models with the progressive scaling strategy,

Reference 83

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Openhermes 2.5: An open dataset of synthetic data for generalist llm assistants., 2023

Reference 84

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 85

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Eyes wide shut? exploring the visual shortcomings of multimodal LLMs

Reference 86

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Document understanding dataset and evalu- ation (dude)

Reference 87

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Reference 88

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning

Reference 89

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought OFA: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework

Reference 90

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 91

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought CogVLM: Visual Expert for Pretrained Language Models

Reference 92

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou

Reference 93

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Chain-of-thought prompting elicits reasoning in large language models

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:42:31.628673Z

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Observation d4241a76-04df-4c98-be96-d1a6782c228f · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

Reference 95

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought V*: Guided visual search as a core mechanism in multimodal LLMs

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:42:31.492476Z

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Observation 14542e57-6b1b-4716-baf2-fca9bf3c314e · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Grok, 2024

Reference 97

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Observation 8cfba54f-0f0b-4c89-bef2-f1b4974ecdf7 · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Florence-2: Advancing a unified representation for a va- riety of vision tasks

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:42:31.210669Z

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Observation 9a22ca37-65b7-40f7-a567-2579d68079d0 · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought Denoising vision trans- formers

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:42:31.042066Z

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Observation a1a23623-bcb0-4da3-874e-c340119c1c88 · outbound

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Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought UniTAB: Unifying text and box outputs for grounded vision-language modeling

Reference 100

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