Efficient Reasoning Distillation: Small Video-Language Models via Synthetic CoT and Difficulty-Aware Fine-Tuning

arXiv:2609.16255 · cs.LG, cs.AI, cs.CV · Submitted 2026-09-14 · Read on arXiv

cs.LG, cs.AI, cs.CV

Submitted: 2026-09-14

Updated: 2026-09-14

Comments: 14 pages, 2 figures, 5 tables. Published in MultiMedia Modeling (MMM 2026), LNCS 16412

Journal ref: MultiMedia Modeling (MMM 2026), Lecture Notes in Computer Science, vol. 16412, pp. 567-580, Springer, Singapore, 2026

DOI: 10.1007/978-981-95-6950-2_40

Code: https://github.com/OpenGVLab/InternVL

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fine-Tuning — 24× in this paper · explained in 5 episodes
• Distillation — 20× in this paper · explained in 2 episodes
• Accuracy — 18× in this paper · explained in 1 episode
• Benchmark — 15× in this paper · explained in 2 episodes
• Generalization — 9× in this paper · explained in 13 episodes
• Chain-of-Thought (CoT) — 5× in this paper · explained in 4 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Synthetic Chain-of-Thought — 4× in this paper
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Data Augmentation — 3× in this paper · explained in 7 episodes
• Edge Deployment — 3× in this paper · explained in 2 episodes
• Knowledge Distillation — 3× in this paper · explained in 11 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 3× in this paper · explained in 5 episodes
• Active Learning — 2× in this paper · explained in 6 episodes
• Edge Devices — 2× in this paper · explained in 2 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Sample Efficiency — 2× in this paper · explained in 4 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Character and Relationship Dynamics — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Setting and Technical Analysis — 1× in this paper
• Structured Reasoning — 1× in this paper · explained in 3 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• PAL: Program-aided Language Models
• A Survey on Video Analytics in Cloud-Edge-Terminal Collaborative Systems
• Generative Adversarial Networks
• On Calibration of Modern Neural Networks
• Distilling the Knowledge in a Neural Network
• Auto-Encoding Variational Bayes
• TVQA: Localized, Compositional Video Question Answering
• Small Models Struggle to Learn from Strong Reasoners
• Improved Baselines with Visual Instruction Tuning
• Decoupled Weight Decay Regularization
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• CinePile: A Long Video Question Answering Dataset and Benchmark
• Playing for Data: Ground Truth from Computer Games
• FitNets: Hints for Thin Deep Nets
• DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
• Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation
• Vision-Language Models for Edge Networks: A Comprehensive Survey
• Training Region-based Object Detectors with Online Hard Example Mining

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