"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth | Paper Citation Record

Observation f1f071cf-2aec-4fcc-971d-435dea073db6 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

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This paper cites Phi-4 Technical Report.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Phi-4 Technical Report

Reference 2

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This paper cites Phi-4-mini technical re- port: Compact yet powerful multimodal language models via mixture-of-loras, 2025.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Phi-4-mini technical re- port: Compact yet powerful multimodal language models via mixture-of-loras, 2025

Reference 3

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This paper cites Cosmos World Foundation Model Platform for Physical AI.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Cosmos World Foundation Model Platform for Physical AI

Reference 4

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This paper cites Pixtral 12B.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Pixtral 12B

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This paper cites System card: Claude opus 4 & claude sonnet 4.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth System card: Claude opus 4 & claude sonnet 4

Reference 6

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Observation d598a7e3-28c1-41a1-a2dd-c0893ee66f47 · outbound

This paper cites Qwen Technical Report.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Qwen Technical Report

Reference 7

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This paper cites Video generation models as world simulators.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Video generation models as world simulators

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This paper cites Language models are few-shot learners.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Language models are few-shot learners

Reference 9

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Observation b1f3c4c2-5d55-43a4-86d3-26d1a5487927 · outbound

This paper cites Spatial memory: how egocentric and allocen- tric combine.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Spatial memory: how egocentric and allocen- tric combine

Reference 10

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This paper cites On learning mechanical laws of motion from video using neu- ral networks.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth On learning mechanical laws of motion from video using neu- ral networks

Reference 11

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This paper cites Spatialvlm: Endow- ing vision-language models with spatial reasoning capabili- ties.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Spatialvlm: Endow- ing vision-language models with spatial reasoning capabili- ties

Reference 12

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This paper cites Visualgpt: Data-efficient adaptation of pretrained language models for image captioning.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Visualgpt: Data-efficient adaptation of pretrained language models for image captioning

Reference 13

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This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 14

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This paper cites ShareGPT4Video: Improving Video Understanding and Generation with Better Captions.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

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

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 16

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This paper cites Spatialrgpt: Grounded spatial reasoning in vision-language models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Spatialrgpt: Grounded spatial reasoning in vision-language models

Reference 17

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This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 18

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This paper cites Sharegpt-4o: Comprehensive multimodal annotations with gpt-4o, 2024.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Sharegpt-4o: Comprehensive multimodal annotations with gpt-4o, 2024

Reference 19

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

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Instructblip: Towards general- purpose vision-language models with instruction tuning,

Reference 20

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This paper cites Myers, and Anna C.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Myers, and Anna C

Reference 21

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 22

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

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth An im- age is worth 16x16 words: Transformers for image recog- nition at scale

Reference 23

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This paper cites Palm-e: An embodied multimodal language model.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Palm-e: An embodied multimodal language model

Reference 24

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This paper cites Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill?.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill?

Reference 25

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This paper cites Large spatial model: End-to-end unposed images to semantic 3d.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Large spatial model: End-to-end unposed images to semantic 3d

Reference 26

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction

Reference 27

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Freyd and Ronald A

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 29

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities

Reference 30

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth MultiModal-GPT: A Vision and Language Model for Dialogue with Humans

Reference 31

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Ego4d: Around the world in 3,000 hours of egocentric video

Reference 32

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Mojito: Motion Trajectory and Intensity Control for Video Generation

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth GPT-4o System Card

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Visual perception of biological motion and a model for its analysis

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth How Good is my Video LMM? Complex Video Reasoning and Robustness Evaluation Suite for Video-LMMs

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth OpenVLA: An Open-Source Vision-Language-Action Model

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Decomposing nerf for editing via feature field distil- lation

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth On space-time interest points

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Denker, Donnie Henderson, Richard E

Reference 41

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Unresolved cited work

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Seed-bench: Bench- marking multimodal large language models

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth LLaVA-OneVision: Easy Visual Task Transfer

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Aria: An Open Multimodal Native Mixture-of-Experts Model

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth VideoChat: Chat-Centric Video Understanding

Reference 46

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Mvbench: A comprehensive multi- modal video understanding benchmark, 2023

Reference 47

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Mvbench: A comprehensive multi-modal video under- standing benchmark

Reference 48

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This paper cites 4k4DGen: Panoramic 4d generation at 4k resolution.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth 4k4DGen: Panoramic 4d generation at 4k resolution

Reference 49

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth VideoEval: Comprehensive Benchmark Suite for Low-Cost Evaluation of Video Foundation Model

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation

Reference 51

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"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Visual instruction tuning

Reference 52

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Observation 165ce984-91ee-4124-a94c-9b16ba99c288 · outbound

This paper cites World model on million-length video and language with ringattention.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth World model on million-length video and language with ringattention

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.744179Z

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Observation 291c6f20-4ded-45c3-9a4a-3a103f693356 · outbound

This paper cites World Model on Million-Length Video And Language With Blockwise RingAttention.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth World Model on Million-Length Video And Language With Blockwise RingAttention

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.397702Z

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Observation 6c44c904-6630-444b-a93f-38ed1f9fe4fd · outbound

This paper cites Mmbench: Is your multi- modal model an all-around player? InEuropean conference on computer vision, pages 216–233.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Mmbench: Is your multi- modal model an all-around player? InEuropean conference on computer vision, pages 216–233

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.700640Z

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Observation 287f2071-c38b-4408-bca7-d5ebe10d9d58 · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.454785Z

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Unavailable: canonical work link unavailable.

Observation c041b85f-11e0-4649-a1f6-71a82fcea3b0 · outbound

This paper cites Vil- bert: Pretraining task-agnostic visiolinguistic representa- tions for vision-and-language tasks.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Vil- bert: Pretraining task-agnostic visiolinguistic representa- tions for vision-and-language tasks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.629617Z

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Observation 007104d2-e26d-473b-8752-e4db07818781 · outbound

This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.517556Z

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Observation afb64a7b-c07f-4719-9763-141effc3091f · outbound

This paper cites Marr and S.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Marr and S

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.589330Z

Source-reported events for the cited work

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Observation 6b4f68f7-8116-44ad-89ab-6b5d4a7f6994 · outbound

This paper cites The llama 4 herd: The beginning of a new era of natively multimodal ai innovation.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth The llama 4 herd: The beginning of a new era of natively multimodal ai innovation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.546692Z

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Observation ee9acb31-5a21-4045-b2e0-84dd3f2f04f2 · outbound

This paper cites Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.629926Z

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Unavailable: canonical work link unavailable.

Observation cc201498-4a27-4b5d-a694-c7e34fa98293 · outbound

This paper cites Sceneteller: Language-to-3d scene gen- eration.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Sceneteller: Language-to-3d scene gen- eration

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.520406Z

Source-reported events for the cited work

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Observation 9e12a8e0-30ad-4cb6-8319-b1eef13414fa · outbound

This paper cites Hello gpt-4o.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Hello gpt-4o

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.496791Z

Source-reported events for the cited work

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Observation e48e9bbf-228b-45ee-9df6-127ffd6cfe68 · outbound

This paper cites A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.737737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfb05f41-d604-4b21-b503-57b6d9b15262 · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth A benchmark dataset and evaluation methodology for video object segmentation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.472155Z

Source-reported events for the cited work

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Observation 2391090d-d87d-400d-9bd7-f7c08548d65a · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth The 2017 DAVIS Challenge on Video Object Segmentation

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.833408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3a638b2-d93a-4774-9347-715607fb7839 · outbound

This paper cites Improving language understanding by gen- erative pre-training.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Improving language understanding by gen- erative pre-training

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:42.867451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b215f03c-825f-42f2-88ea-f621eb58ee81 · outbound

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

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Learning transferable visual models from natural language supervision

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.419855Z

Source-reported events for the cited work

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Observation 0edd3b06-3c2d-4fae-b78a-5e2fa30ec67b · outbound

This paper cites Learning to localize objects improves spatial reasoning in visual-llms.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Learning to localize objects improves spatial reasoning in visual-llms

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.392314Z

Source-reported events for the cited work

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Observation 258f258f-96af-4869-b33a-356421b41a63 · outbound

This paper cites Two-stream con- volutional networks for action recognition in videos.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Two-stream con- volutional networks for action recognition in videos

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.363739Z

Source-reported events for the cited work

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Observation 2b934dd0-5e70-4709-a7b7-a2cdfd52d1d2 · outbound

This paper cites Spelke and Katherine D.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Spelke and Katherine D

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.334671Z

Source-reported events for the cited work

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Observation 295e2f7d-6221-4401-874a-24cfa57b4430 · outbound

This paper cites AlanaVLM: A Multimodal Embodied AI Foundation Model for Egocentric Video Understanding.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth AlanaVLM: A Multimodal Embodied AI Foundation Model for Egocentric Video Understanding

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.060746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7d1d6da-3a47-4bef-b35e-32e8ae21851d · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.093882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a5aaa99-b645-43bc-8af9-676c66a43840 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth LLaMA: Open and Efficient Foundation Language Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.113406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f7dbdb7-394a-4ae0-b3bb-6bc41b0c7e9f · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Wan: Open and Advanced Large-Scale Video Generative Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.137692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc84dc86-fffc-4bb6-a501-fa250f00a15e · outbound

This paper cites Vlm see, robot do: Human demo video to robot action plan via vision language model.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Vlm see, robot do: Human demo video to robot action plan via vision language model

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.151243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa8b9b52-e827-4c28-9578-a50ed701759b · outbound

This paper cites Action recognition by dense trajectories.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Action recognition by dense trajectories

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.312882Z

Source-reported events for the cited work

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Observation cccf61d6-12aa-4df8-8839-8fd1fec4e665 · outbound

This paper cites Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.184734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10e7b47a-78ab-49c0-95f1-6e1e62c5e8eb · outbound

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

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.206113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99c81a13-f048-40d2-899f-0c83adb03880 · outbound

This paper cites Compositional 4D Dynamic Scenes Understanding with Physics Priors for Video Question Answering.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Compositional 4D Dynamic Scenes Understanding with Physics Priors for Video Question Answering

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.220820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20e48f69-4aef-4938-b4d6-3c175f058657 · outbound

This paper cites Internvideo2: Scaling foundation models for multimodal video understanding.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Internvideo2: Scaling foundation models for multimodal video understanding

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.286356Z

Source-reported events for the cited work

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Observation 537ae9d2-8b8b-4ee2-87fc-d2868ca37de7 · outbound

This paper cites InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.265563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f134dadd-448a-445f-b22d-585eb2cb4012 · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Finetuned Language Models Are Zero-Shot Learners

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.284513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5138e12-3483-4ac6-be7a-b50acc9991b9 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large lan- guage models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Chain-of-thought prompting elicits reasoning in large lan- guage models

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.261004Z

Source-reported events for the cited work

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Observation 0cd03c21-2593-429e-8bec-9ac98adc859a · outbound

This paper cites Cat4d: Create anything in 4d with multi-view video dif- fusion models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Cat4d: Create anything in 4d with multi-view video dif- fusion models

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.218328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7160c7a-c7a5-458d-a04c-a6eae5b201f6 · outbound

This paper cites Videollm-mod: Efficient video-language streaming with mixture-of-depths vision computation.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Videollm-mod: Efficient video-language streaming with mixture-of-depths vision computation

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.180077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7f35551c-ecd8-4cff-a24f-7728b9494dc9 · outbound

This paper cites Grok-2 beta release.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Grok-2 beta release

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.141281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1d90920f-1b08-41ef-bfce-515c793042e0 · outbound

This paper cites Youtube-vos: Sequence-to-sequence video object segmentation.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Youtube-vos: Sequence-to-sequence video object segmentation

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.097944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 606858c2-5ba7-46d1-bbc4-ffddb62bf66a · outbound

This paper cites Qwen2.5 Technical Report.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Qwen2.5 Technical Report

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.382032Z

Source-reported events for the cited work

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Observation 95d4376c-3934-4314-a91e-ead34624e971 · outbound

This paper cites Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.397444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ad127a-1794-4c9e-804a-97320756cfe1 · outbound

This paper cites VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.413008Z

Source-reported events for the cited work

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Observation 103a44c8-9f74-48c6-a7f4-5d97de0f827e · outbound

This paper cites Mmmu: A massive multi- discipline multimodal understanding and reasoning bench- mark for expert agi.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Mmmu: A massive multi- discipline multimodal understanding and reasoning bench- mark for expert agi

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.060349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7adae322-2bbc-4379-9266-96a88d33e9cb · outbound

This paper cites Improving 2d feature representations by 3d-aware fine-tuning.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Improving 2d feature representations by 3d-aware fine-tuning

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:45.027303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4f7e4cd0-553d-4913-9e09-bc9d62d25270 · outbound

This paper cites VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.457093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 464e317c-2c03-4f2c-989e-770bb2eae1f8 · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.465975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e46c5ca-e39f-423b-bf57-5fc576902e71 · outbound

This paper cites COMBO: Compositional World Models for Embodied Multi-Agent Cooperation.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth COMBO: Compositional World Models for Embodied Multi-Agent Cooperation

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.481167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da04b8eb-6d9d-405c-8451-46e7f320f046 · outbound

This paper cites Llava-next: A strong zero-shot video understanding model,.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Llava-next: A strong zero-shot video understanding model,

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.495708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 391f0e94-7cc2-4f5a-802d-bf20799a183f · outbound

This paper cites MMVU: Measuring Expert-Level Multi-Discipline Video Understanding.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-06T05:15:43.506493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab63a895-6cea-438b-9c36-efb8f427e55f · outbound

This paper cites Lla- mafactory: Unified efficient fine-tuning of 100+ language models.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Lla- mafactory: Unified efficient fine-tuning of 100+ language models

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:44.978143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c7047aff-277d-48b2-86f3-09145a99fdef · outbound

This paper cites Feature 3dgs: Supercharging 3d gaussian splatting to enable distilled fea- ture fields.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Feature 3dgs: Supercharging 3d gaussian splatting to enable distilled fea- ture fields

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:15:44.936347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

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