FedCoT-VQA: A Federated Learning and Unlearning Framework for Chain-of-Thought Planners in VideoQA

arXiv:2609.26814 · cs.CR · Submitted 2026-09-18 · Read on arXiv

cs.CR

Submitted: 2026-09-18

Updated: 2026-09-18

Terminology

• Trace — 44× in this paper · explained in 2 episodes
• Adaptation — 42× in this paper · explained in 1 episode
• Aggregation — 29× in this paper · explained in 1 episode
• Federated Learning — 26× in this paper · explained in 15 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• Grounding — 11× in this paper · explained in 3 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Temporal Reasoning — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Data Heterogeneity — 3× in this paper · explained in 3 episodes
• Local Optimization — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Chain-of-Thought (CoT) — 2× in this paper · explained in 4 episodes
• Federated Learning (FL) — 2× in this paper · explained in 7 episodes
• Machine Unlearning — 2× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning — 2× in this paper · explained in 2 episodes
• Reasoning Traces — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Approximate Unlearning — 1× in this paper · explained in 1 episode
• Chain-of-Thought (CoT) Reasoning — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Fisher Information — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Influence Functions — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Non-IID Data — 1× in this paper · explained in 2 episodes
• Planner-Side Partitioning for Federated Training — 1× in this paper
• Residual Unlearning Module for Client Deletion — 1× in this paper
• Server-Side Aggregation for Reasoning Preservation — 1× in this paper
• Spatio-temporal grounding — 1× in this paper · explained in 2 episodes

Sources

• Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
• Frame-Voyager: Learning to Query Frames for Video Large Language Models
• M-LLM Based Video Frame Selection for Efficient Video Understanding
• Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs
• Towards Sparse Video Understanding and Reasoning
• Weakly Supervised Temporal Adjacent Network for Language Grounding
• Stochastic subgradient method converges at the rate $O(k^{-1/4})$ on weakly convex functions
• Flower: A Friendly Federated Learning Research Framework
• STAR: A Benchmark for Situated Reasoning in Real-World Videos
• FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition
• InternVideo: General Video Foundation Models via Generative and Discriminative Learning
• CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Representation Alignment
• ChatVideo: A Tracklet-centric Multimodal and Versatile Video Understanding System

Related papers

• SoK: AI-Augmented Binary Reversing
• Relaxed Sender Anonymity for CBDC Interbank Settlement: A Zero-Knowledge Approach on Permissioned EVM
• Calibration-Family Overfit: Why Trusted Sabotage Monitors Don't Transfer Across Lineages
• Efficient Fuzzy PSI under One-Sided Assumptions
• Sealing the Audit-Runtime Gap for LLM Skills
• Token Composition: A Graph Based on EVM Logs