Text4Seg++: Advancing Image Segmentation via Generative Language Modeling | Paper Citation Record

Observation 716f03b8-86ab-4e08-8c8d-74761c3720c9 · outbound

This paper cites A survey on multimodal large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling A survey on multimodal large language models,

Reference 1

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Observation 0f62a146-a2f4-4d63-9bc6-f5571e8f2534 · outbound

This paper cites Visual instruction tuning,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Visual instruction tuning,

Reference 2

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Observation 8dc1dd1d-1d75-4478-99a3-d81a985a0b0c · outbound

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Deepseek- vl: Towards real-world vision-language understanding,

Reference 3

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Observation b1d28aa1-1afb-47d4-89ab-1b0f6dd3b58c · outbound

This paper cites Improved baselines with visual instruction tuning,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Improved baselines with visual instruction tuning,

Reference 4

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Observation 4d2d77bb-cbc9-4ddb-b413-26d7105d731f · outbound

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 5

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites,

Reference 6

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Observation caee47b3-16b0-426b-83da-88d573f67b5c · outbound

This paper cites Moma: Multimodal llm adapter for fast personalized image generation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Moma: Multimodal llm adapter for fast personalized image generation,

Reference 7

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This paper cites Genartist: Multimodal llm as an agent for unified image generation and editing,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Genartist: Multimodal llm as an agent for unified image generation and editing,

Reference 8

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Observation f1d1bcbb-da5a-485d-80d1-2c248c5cca09 · outbound

This paper cites Visionllm: Large language model is also an open-ended decoder for vision-centric tasks,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Visionllm: Large language model is also an open-ended decoder for vision-centric tasks,

Reference 9

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Observation b331bf85-980c-48c2-9934-994d1a0e9ce7 · outbound

This paper cites Groma: Localized visual tokenization for grounding multimodal large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Groma: Localized visual tokenization for grounding multimodal large language models,

Reference 10

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Observation 94569e89-143d-482b-b03f-8cb59540ccbe · outbound

This paper cites Towards open vocabulary learning: A survey,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Towards open vocabulary learning: A survey,

Reference 11

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Observation 8b45ef7e-c52e-4f57-bdae-c0cd4a2de9df · outbound

This paper cites NExT-Chat: An LMM for Chat, Detection and Segmentation.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling NExT-Chat: An LMM for Chat, Detection and Segmentation

Reference 12

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Observation c90b2773-5ec2-4b61-b6bc-3826548b16ba · outbound

This paper cites Transformer-based visual segmentation: A survey,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Transformer-based visual segmentation: A survey,

Reference 13

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Observation 4cae6a04-e525-4a39-8aec-5334820936e0 · outbound

This paper cites Smooseg: smoothness prior for unsupervised semantic segmentation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Smooseg: smoothness prior for unsupervised semantic segmentation,

Reference 14

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Observation 4c81b0c7-3da7-41b1-a837-d777d9576340 · outbound

This paper cites Lisa: Reasoning segmentation via large language model,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Lisa: Reasoning segmentation via large language model,

Reference 15

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This paper cites Gsva: Generalized segmentation via multimodal large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Gsva: Generalized segmentation via multimodal large language models,

Reference 16

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This paper cites Groundhog: Grounding large language models to holistic segmentation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Groundhog: Grounding large language models to holistic segmentation,

Reference 17

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Observation d4bfe972-1a09-4597-adb3-ad423ed28433 · outbound

This paper cites Multi-modal instruction tuned llms with fine-grained visual perception,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Multi-modal instruction tuned llms with fine-grained visual perception,

Reference 18

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Observation c682b7c6-6b0b-431b-b2b6-d712e43d3a44 · outbound

This paper cites Pixellm: Pixel reasoning with large multimodal model,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Pixellm: Pixel reasoning with large multimodal model,

Reference 19

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Observation 8d824f5d-66f3-4eb5-920f-0e1ba053b51e · outbound

This paper cites Glamm: Pixel grounding large multimodal model,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Glamm: Pixel grounding large multimodal model,

Reference 20

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Observation 4b0231c8-78cc-47bb-bd3a-4d8fb6362b3f · outbound

This paper cites Segment anything,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Segment anything,

Reference 21

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Observation 2757456d-95a0-4a9d-8364-b9ccd471cf09 · outbound

This paper cites Jack of all tasks master of many: Designing general-purpose coarse-to-fine vision-language model,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Jack of all tasks master of many: Designing general-purpose coarse-to-fine vision-language model,

Reference 22

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Observation 8ce7c468-7c2d-4911-b0df-892351472ea5 · outbound

This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Florence-2: Advancing a unified representation for a variety of vision tasks,

Reference 23

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This paper cites Visionllm v2: An end-to-end generalist multimodal large language model for hundreds of vision-language tasks,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Visionllm v2: An end-to-end generalist multimodal large language model for hundreds of vision-language tasks,

Reference 24

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Observation 2c00a354-3c52-442e-95d3-202f7297586f · outbound

This paper cites Text4seg: Reimagining image segmentation as text generation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Text4seg: Reimagining image segmentation as text generation,

Reference 25

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Observation 3340fec4-8112-4d05-b5d3-b798fd76bfaf · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 26

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Observation 89d2949c-35d2-43a8-b989-53a6f514d1df · outbound

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 27

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Observation a42fe197-fe8a-4913-9466-e31f781d7447 · outbound

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 28

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Observation 82cff4a6-f430-488c-b07e-fa39a01ab7d9 · outbound

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 29

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Observation edecca24-37f4-4c2e-9ca0-c4797a88165d · outbound

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Flamingo: a visual language model for few-shot learning,

Reference 30

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This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 31

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This paper cites Otter: A multi-modal model with in-context instruction tun- ing,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Otter: A multi-modal model with in-context instruction tun- ing,

Reference 32

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This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,

Reference 33

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This paper cites InstructBLIP: Towards general-purpose vision-language models with instruction tuning,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling InstructBLIP: Towards general-purpose vision-language models with instruction tuning,

Reference 34

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Observation dc0a4841-5d66-46b6-b9dd-a889b2aad7f5 · outbound

This paper cites mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration,

Reference 35

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This paper cites Llava-next: Improved reasoning, ocr, and world knowledge,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Llava-next: Improved reasoning, ocr, and world knowledge,

Reference 36

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This paper cites Llava-uhd: an lmm perceiving any aspect ratio and high-resolution images,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Llava-uhd: an lmm perceiving any aspect ratio and high-resolution images,

Reference 37

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This paper cites LLaV A-onevision: Easy visual task transfer,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling LLaV A-onevision: Easy visual task transfer,

Reference 38

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This paper cites Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Reference 39

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This paper cites Monkey: Image resolution and text label are important things for large multi-modal models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Monkey: Image resolution and text label are important things for large multi-modal models,

Reference 40

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This paper cites Sphinx: A mixer of weights, visual embeddings and image scales for multi-modal large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Sphinx: A mixer of weights, visual embeddings and image scales for multi-modal large language models,

Reference 41

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This paper cites InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models

Reference 42

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 43

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Observation c6acb05d-fd47-4252-bbd5-d27fcc0f1210 · outbound

This paper cites Qwen2.5-VL Technical Report.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Qwen2.5-VL Technical Report

Reference 44

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This paper cites Omg-llava: Bridging image-level, object-level, pixel-level reasoning and understanding,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Omg-llava: Bridging image-level, object-level, pixel-level reasoning and understanding,

Reference 45

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This paper cites MMR: A large-scale benchmark dataset for multi-target and multi-granularity reasoning segmentation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling MMR: A large-scale benchmark dataset for multi-target and multi-granularity reasoning segmentation,

Reference 46

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This paper cites SegLLM: Multi-round reasoning segmentation with large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling SegLLM: Multi-round reasoning segmentation with large language models,

Reference 47

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Observation 9e40fef4-cb57-4c04-9145-434de89ae1fb · outbound

This paper cites SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model

Reference 48

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This paper cites Geopix: A multimodal large language model for pixel-level image understanding in remote sensing,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Geopix: A multimodal large language model for pixel-level image understanding in remote sensing,

Reference 49

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This paper cites Ufo: A unified approach to fine-grained visual perception via open-ended language interface,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Ufo: A unified approach to fine-grained visual perception via open-ended language interface,

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This paper cites Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding

Reference 51

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This paper cites HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with Large Multimodal Model.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with Large Multimodal Model

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This paper cites Alto: Adaptive-length tokenizer for autoregressive mask generation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Alto: Adaptive-length tokenizer for autoregressive mask generation,

Reference 53

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This paper cites Pix2seq: A language modeling framework for object detection,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Pix2seq: A language modeling framework for object detection,

Reference 54

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Observation fe671d6a-c133-46d4-b53b-5648672120c8 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Grounding dino: Marrying dino with grounded pre-training for open-set object detection,

Reference 55

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Universal instance perception as object discovery and retrieval,

Reference 56

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Grounding multimodal large language models to the world,

Reference 57

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

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 58

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Vitron: A unified pixel-level vision llm for understanding, generating, segmenting, edit- ing,

Reference 59

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This paper cites Learning transferable visual models from natural language supervision,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Learning transferable visual models from natural language supervision,

Reference 60

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This paper cites Sigmoid loss for language image pre-training,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Sigmoid loss for language image pre-training,

Reference 61

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This paper cites Qwen3 Technical Report.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Qwen3 Technical Report

Reference 62

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling LLaMA: Open and Efficient Foundation Language Models

Reference 63

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This paper cites Referitgame: Referring to objects in photographs of natural scenes,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Referitgame: Referring to objects in photographs of natural scenes,

Reference 64

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Run-length encodings (corresp.),

Reference 65

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This paper cites LoRA: Low-rank adaptation of large language models,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling LoRA: Low-rank adaptation of large language models,

Reference 66

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling SAMRefiner: Taming segment anything model for universal mask refinement,

Reference 67

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Swift: A scalable lightweight infrastructure for fine-tuning,

Reference 68

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Decoupled weight decay regularization,

Reference 69

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Zero: Memory optimizations toward training trillion parameter models,

Reference 70

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This paper cites Phrasecut: Language- based image segmentation in the wild,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Phrasecut: Language- based image segmentation in the wild,

Reference 71

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Gres: Generalized referring expression segmentation,

Reference 72

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Generation and comprehension of unambiguous object descriptions,

Reference 73

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Polyformer: Referring image segmentation as sequential polygon generation,

Reference 74

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Language-aware vision transformer for referring segmentation,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:22:12.636010Z

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Sam4mllm: Enhance multi-modal large language model for referring expression segmentation,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:22:12.624866Z

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Segagent: Exploring pixel understanding capabilities in mllms by imitating human annotator trajectories,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:22:12.612245Z

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Popen: Preference-based optimization and ensemble for lvlm-based reasoning segmentation,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:22:12.600552Z

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Microsoft coco: Common objects in context,

Reference 79

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Pix2Cap-COCO: Advancing Visual Comprehension via Pixel-Level Captioning

Reference 80

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Rotated multi-scale interaction network for referring remote sensing image seg- mentation,

Reference 81

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

Reference 82

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Clearclip: Decomposing clip representations for dense vision-language inference,

Reference 83

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Proxyclip: Proxy attention improves clip for open-vocabulary segmentation,

Reference 84

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Open-vocabulary universal image seg- mentation with maskclip,

Reference 85

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Groupvit: Semantic segmentation emerges from text supervision,

Reference 86

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Open-vocabulary semantic segmentation with mask-adapted clip,

Reference 87

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This paper cites San: side adapter network for open-vocabulary semantic segmentation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling San: side adapter network for open-vocabulary semantic segmentation,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:22:12.513496Z

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling LaSagnA: Language-based Segmentation Assistant for Complex Queries

Reference 89

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This paper cites GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding

Reference 90

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Semantic understanding of scenes through the ade20k dataset,

Reference 91

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Text4Seg++: Advancing Image Segmentation via Generative Language Modeling The role of context for object detection and semantic segmentation in the wild,

Reference 92

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This paper cites The pascal visual object classes challenge 2007,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling The pascal visual object classes challenge 2007,

Reference 93

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Observation 01d8ea53-ab5f-4988-bb0a-26d37fc44b82 · outbound

This paper cites Side adapter network for open-vocabulary semantic segmentation,.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Side adapter network for open-vocabulary semantic segmentation,

Reference 94

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This paper cites Available: https://openreview.net/forum?id=lLmqxkfSIw.

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling Available: https://openreview.net/forum?id=lLmqxkfSIw

Reference 2024

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