VidHarness: Evolving Agent Harnesses for Cost-Efficient Long Video Understanding

arXiv:2609.38413 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Accuracy — 49× in this paper · explained in 1 episode
• Fidelity — 25× in this paper · explained in 2 episodes
• Benchmark — 15× in this paper · explained in 2 episodes
• Trace — 11× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 7× in this paper
• Monte Carlo Tree Search — 5× in this paper
• Adam — 4× in this paper · explained in 2 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Iterative Refinement — 4× in this paper · explained in 3 episodes
• Agentic System — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Vision-language models — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 2× in this paper
• Causal Inference — 2× in this paper · explained in 4 episodes
• Elias — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Agent Harness — 1× in this paper · explained in 2 episodes
• Agent Skills — 1× in this paper · explained in 1 episode
• Agentic Approaches — 1× in this paper · explained in 1 episode
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Agentic Search — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Qwen2.5-VL Technical Report
• FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
• HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry
• Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1
• Video-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning?
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• MetaVideoAgent: Automated Video-Agent Evolution for Long-Form Video Understanding
• Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution
• From Question Answering to Task Completion: A Survey on Agent System and Harness Design
• GPT-4o System Card
• AIDE: AI-Driven Exploration in the Space of Code
• Meta-Harness: End-to-End Optimization of Model Harnesses
• VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning
• AutoHarness: improving LLM agents by automatically synthesizing a code harness
• Recursive Agent Harnesses
• AlphaEvolve: A coding agent for scientific and algorithmic discovery
• MR. Video: "MapReduce" is the Principle for Long Video Understanding
• LLM-as-Code: Agentic Programming for Agent Harness
• Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

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