VideoLLM Benchmarks and Evaluation: A Survey
Fuente:
arXiv
Saved in:
| Main Author: | Kumar, Yogesh |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sharp Eyes and Memory for VideoLLMs: Information-Aware Visual Token Pruning for Efficient and Reliable VideoLLM Reasoning
by: Qin, Jialong, et al.
Published: (2025)
by: Qin, Jialong, et al.
Published: (2025)
Language-Guided Temporal Token Pruning for Efficient VideoLLM Processing
by: Kumar, Yogesh
Published: (2025)
by: Kumar, Yogesh
Published: (2025)
VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning
by: Li, Chenglin, et al.
Published: (2026)
by: Li, Chenglin, et al.
Published: (2026)
IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes
by: Liang, Yujia, et al.
Published: (2025)
by: Liang, Yujia, et al.
Published: (2025)
Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
by: Wang, Haibo, et al.
Published: (2024)
by: Wang, Haibo, et al.
Published: (2024)
Geometry-Guided Camera Motion Understanding in VideoLLMs
by: Feng, Haoan, et al.
Published: (2026)
by: Feng, Haoan, et al.
Published: (2026)
Temporal Object-Aware Vision Transformer for Few-Shot Video Object Detection
by: Kumar, Yogesh, et al.
Published: (2025)
by: Kumar, Yogesh, et al.
Published: (2025)
"I Can See Forever!": Evaluating Real-time VideoLLMs for Assisting Individuals with Visual Impairments
by: Zhang, Ziyi, et al.
Published: (2025)
by: Zhang, Ziyi, et al.
Published: (2025)
On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes
by: Modi, Rajat, et al.
Published: (2024)
by: Modi, Rajat, et al.
Published: (2024)
Lost in Time: A New Temporal Benchmark for VideoLLMs
by: Cores, Daniel, et al.
Published: (2024)
by: Cores, Daniel, et al.
Published: (2024)
VideoCogQA: A Controllable Benchmark for Evaluating Cognitive Abilities in Video-Language Models
by: Li, Chenglin, et al.
Published: (2024)
by: Li, Chenglin, et al.
Published: (2024)
Bridging Text and Video Generation: A Survey
by: Kumar, Nilay, et al.
Published: (2025)
by: Kumar, Nilay, et al.
Published: (2025)
AEGIS: Authenticity Evaluation Benchmark for AI-Generated Video Sequences
by: Li, Jieyu, et al.
Published: (2025)
by: Li, Jieyu, et al.
Published: (2025)
ViBe: A Text-to-Video Benchmark for Evaluating Hallucination in Large Multimodal Models
by: Rawte, Vipula, et al.
Published: (2024)
by: Rawte, Vipula, et al.
Published: (2024)
VideoLLM-online: Online Video Large Language Model for Streaming Video
by: Chen, Joya, et al.
Published: (2024)
by: Chen, Joya, et al.
Published: (2024)
MT-Video-Bench: A Holistic Video Understanding Benchmark for Evaluating Multimodal LLMs in Multi-Turn Dialogues
by: Pan, Yaning, et al.
Published: (2025)
by: Pan, Yaning, et al.
Published: (2025)
A Survey on Generative AI and LLM for Video Generation, Understanding, and Streaming
by: Zhou, Pengyuan, et al.
Published: (2024)
by: Zhou, Pengyuan, et al.
Published: (2024)
SLVMEval: Synthetic Meta Evaluation Benchmark for Text-to-Long Video Generation
by: Matsuda, Ryosuke, et al.
Published: (2026)
by: Matsuda, Ryosuke, et al.
Published: (2026)
EGOILLUSION: Benchmarking Hallucinations in Egocentric Video Understanding
by: Seth, Ashish, et al.
Published: (2025)
by: Seth, Ashish, et al.
Published: (2025)
Punching Bag vs. Punching Person: Motion Transferability in Videos
by: Abdullah, Raiyaan, et al.
Published: (2025)
by: Abdullah, Raiyaan, et al.
Published: (2025)
CrossVid: A Comprehensive Benchmark for Evaluating Cross-Video Reasoning in Multimodal Large Language Models
by: Li, Jingyao, et al.
Published: (2025)
by: Li, Jingyao, et al.
Published: (2025)
VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation
by: Jiang, Longteng, et al.
Published: (2026)
by: Jiang, Longteng, et al.
Published: (2026)
Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLM
by: Wang, Han, et al.
Published: (2024)
by: Wang, Han, et al.
Published: (2024)
VideoGUI: A Benchmark for GUI Automation from Instructional Videos
by: Lin, Kevin Qinghong, et al.
Published: (2024)
by: Lin, Kevin Qinghong, et al.
Published: (2024)
A Survey: Spatiotemporal Consistency in Video Generation
by: Yin, Zhiyu, et al.
Published: (2025)
by: Yin, Zhiyu, et al.
Published: (2025)
Segment Anything for Videos: A Systematic Survey
by: Zhang, Chunhui, et al.
Published: (2024)
by: Zhang, Chunhui, et al.
Published: (2024)
Proact-VL: A Proactive VideoLLM for Real-Time AI Companions
by: Yan, Weicai, et al.
Published: (2026)
by: Yan, Weicai, et al.
Published: (2026)
Video-Bench: Human-Aligned Video Generation Benchmark
by: Han, Hui, et al.
Published: (2025)
by: Han, Hui, et al.
Published: (2025)
A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction
by: Chen, Yongfan, et al.
Published: (2025)
by: Chen, Yongfan, et al.
Published: (2025)
MMSI-Video-Bench: A Holistic Benchmark for Video-Based Spatial Intelligence
by: Lin, Jingli, et al.
Published: (2025)
by: Lin, Jingli, et al.
Published: (2025)
Distorted or Fabricated? A Survey on Hallucination in Video LLMs
by: Huang, Yiyang, et al.
Published: (2026)
by: Huang, Yiyang, et al.
Published: (2026)
A Survey on Backbones for Deep Video Action Recognition
by: Tang, Zixuan, et al.
Published: (2024)
by: Tang, Zixuan, et al.
Published: (2024)
A Survey of Video Datasets for Grounded Event Understanding
by: Sanders, Kate, et al.
Published: (2024)
by: Sanders, Kate, et al.
Published: (2024)
H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding
by: Wu, Qi, et al.
Published: (2025)
by: Wu, Qi, et al.
Published: (2025)
GaitCrafter: Diffusion Model for Biometric Preserving Gait Synthesis
by: Mitra, Sirshapan, et al.
Published: (2025)
by: Mitra, Sirshapan, et al.
Published: (2025)
SCBench: A Sports Commentary Benchmark for Video LLMs
by: Ge, Kuangzhi, et al.
Published: (2024)
by: Ge, Kuangzhi, et al.
Published: (2024)
SONIC-O1: A Real-World Benchmark for Evaluating Multimodal Large Language Models on Audio-Video Understanding
by: Radwan, Ahmed Y., et al.
Published: (2026)
by: Radwan, Ahmed Y., et al.
Published: (2026)
VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding
by: Chen, Houlun, et al.
Published: (2024)
by: Chen, Houlun, et al.
Published: (2024)
HumanVideo-MME: Benchmarking MLLMs for Human-Centric Video Understanding
by: Cai, Yuxuan, et al.
Published: (2025)
by: Cai, Yuxuan, et al.
Published: (2025)
How to Enable LLM with 3D Capacity? A Survey of Spatial Reasoning in LLM
by: Zha, Jirong, et al.
Published: (2025)
by: Zha, Jirong, et al.
Published: (2025)
Similar Items
-
Sharp Eyes and Memory for VideoLLMs: Information-Aware Visual Token Pruning for Efficient and Reliable VideoLLM Reasoning
by: Qin, Jialong, et al.
Published: (2025) -
Language-Guided Temporal Token Pruning for Efficient VideoLLM Processing
by: Kumar, Yogesh
Published: (2025) -
VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning
by: Li, Chenglin, et al.
Published: (2026) -
IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes
by: Liang, Yujia, et al.
Published: (2025) -
Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
by: Wang, Haibo, et al.
Published: (2024)