Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework | Paper Citation Record

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summa- rization

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: 2016 IEEE International Conference on Image Processing (ICIP)

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Eu- ropean Conference on Computer Vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European conference on computer vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework MOT20: A benchmark for multi object tracking in crowded scenes

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the Computer Vision and Pattern Recognition Conference

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Advances in Neural Information Processing Systems36, 27092–27112 (2023) 2

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the Computer Vision and Pattern Recognition Conference

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework YOLOX: Exceeding YOLO Series in 2021

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: ICLR

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Scaling Laws for Neural Language Models

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework LLaVA-OneVision: Easy Visual Task Transfer

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework OVTR: End-to-End Open-Vocabulary Multiple Object Tracking with Transformer

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Science China Information Sciences 68(10), 200102 (2025) 4

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European conference on computer vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European Conference on Computer Vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework IEEE Transactions on Industrial Informatics pp

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework IEEE Transactions on Industrial Informatics (2025) 7, 10

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European conference on computer vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework International journal of computer vision129, 548–578 (2021) 11

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework arXiv preprint arXiv:2511.17681 (2025) 1, 4

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: 2023 IEEE International conference on image processing (ICIP)

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Available at SSRN 5541079 (2025) 1

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework IEEE transactions on pattern analysis and machine intelligence39(6), 1137–1149 (2016) 9, 12

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recog- nition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European conference on computer vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework TransTrack: Multiple Object Tracking with Transformer

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European Conference on Computer Vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Neural computation1(2), 270–280 (1989) 26

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: 2017 IEEE international conference on image processing (ICIP)

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the ieee/cvf conference on computer vision and pattern recognition

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Qwen3 Technical Report

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European conference on computer vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European Conference on Computer Vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework GLM-5: from Vibe Coding to Agentic Engineering

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European Conference on Computer Vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: Proceedings of the 33rd ACM International Confer- ence on Multimedia

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Observation c10f3d70-cbf7-4bd7-a5fa-4902dd47f503 · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework In: European conference on computer vision

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework arXiv preprint arXiv:2510.13235 (2025) 1, 4

Reference 66

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework interaction

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework For example, a single GT cyclist (ID 73) might be predicted as two separate tracked IDs (ID 3 and ID 6)

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Under standard protocols, the absence of a prediction would result in a zero score for the corresponding GT caption, dragging down the overall semantic average

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Based on the provided video frames and the orig- inal instance caption, generate a more detailed description for this specific instance (object/person/animal)

Reference 74

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Unresolved cited work

Reference 78

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework appears to

Reference 79

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Observation c33b8571-253d-48c2-b508-1cc9a45945fa · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Do not browse the web or read external files

Reference 80

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Observation 270918c6-575f-44ae-8fd8-37821f51ff5f · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework No markdown, no prose

Reference 81

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Decimal values are allowed

Reference 82

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Observation 75b8169c-39fc-47d8-9a59-927b7fe8f234 · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Author et al

Reference 83

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Observation 88fa096b-4eff-451b-8ff8-3378a8b5845e · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Your task is to compare the predicted description with the correct description and determine its level of detail, considering both completeness and specificity

Reference 84

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Observation add000b2-9537-457c-83dc-71124a73403d · outbound

This paper cites Your task is to compare the predicted description with the correct description and determine if the generated response aligns with the overall context of the video content.

Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Your task is to compare the predicted description with the correct description and determine if the generated response aligns with the overall context of the video content

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-03T11:28:14.635010Z

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Observation 24c4281c-0918-4be7-b0ec-94188875017e · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework Your task is to compare the predicted description with the correct description and determine if they correctly reflect the temporal sequence of events in the video content

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-03T11:28:14.719954Z

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Observation fe80128f-4c58-4ab9-a746-c7dcef81e240 · outbound

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Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework You will be given two very similar questions, a common correct description and predicted descriptions for the two questions

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T11:28:14.840283Z

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