Grounded Product Understanding in Livestream Videos

arXiv:2609.20508 · cs.CV · Submitted 2026-09-17 · Read on arXiv

cs.CV

Submitted: 2026-09-17

Updated: 2026-09-28

Terminology

• Grounding — 15× in this paper · explained in 3 episodes
• Benchmark — 14× in this paper · explained in 2 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Grounded Product Understanding Benchmark — 1× in this paper
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Qwen2.5-VL Technical Report
• Qwen3-VL Technical Report
• Spatiotemporal Graph Guided Multi-modal Network for Livestreaming Product Retrieval
• Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
• TimeScope: Towards Task-Oriented Temporal Grounding In Long Videos
• E-VAds: An E-commerce Short Videos Understanding Benchmark for MLLMs
• GPT-4o System Card
• LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding
• SynopGround: A Large-Scale Dataset for Multi-Paragraph Video Grounding from TV Dramas and Synopses
• SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
• InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling
• FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model
• VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding
• Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese
• MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
• MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval
• GME: Improving Universal Multimodal Retrieval by Multimodal LLMs
• InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

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