Grounding with Confidence: Controllable Generative Video Temporal Grounding

arXiv:2609.39883 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-10-08

Terminology

• Grounding — 35× in this paper · explained in 3 episodes
• Verifier — 25× in this paper · explained in 2 episodes
• Calibration — 13× in this paper · explained in 7 episodes
• Actor — 12× in this paper · explained in 3 episodes
• Adaptation — 8× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Decode — 8× in this paper · explained in 2 episodes
• Online Adaptation — 4× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• GRPO — 3× in this paper · explained in 6 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Frozen model — 2× in this paper · explained in 2 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hallucination Detection — 1× in this paper · explained in 2 episodes
• IEEE International Conference on Computer Vision — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• CAVE: Competence-Aware Visual Boundary Evidence Alignment for Video Temporal Grounding
• Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs
• Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
• Towards One-to-Many Temporal Grounding
• TimeLens2: Generalist Video Temporal Grounding with Multimodal LLMs

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