Derived from arXiv:2607.18080 - Sparse Evidence Can Suffice: Agentic Evidence Seeking for Multimodal Video Misinformation Detection
Scanned 9/11/2026
Install to Claude Code
npx -y skills add hiyenwong/ai_collection --skill sparse-evidence-can-suffice-agentic-evidence-seeki --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Sparse Evidence Can Suffice Agentic Evidence Seeki?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/hiyenwong-sparse-evidence-can-suffice-agentic-evidence-seeki)More formats (shields.io, HTML) on the badges page.
# Sparse Evidence Can Suffice: Agentic Evidence Seeking for Multimodal Video Misinformation Detection
Derived from arXiv:2607.18080 - Sparse Evidence Can Suffice: Agentic Evidence Seeking for Multimodal Video Misinformation Detection
## Core Concept
Multimodal video misinformation detection is commonly formulated as a holistic video-understanding task, where the entire video and its associated content are processed and judged in a single pass. However, real-world misinformation often exhibits a sparse and compositional evidence structure: a reliable decision may depend on only a few coupled clues, while most video content contributes limited additional information. Exhaustive multimodal reasoning may therefore introduce substantial redundan...
## Key Insights
- Derived from arXiv:2607.18080
- Published: 2026-07-20
- Utility Score: 1.00
- Authors: Haochen Zhao, Yongxiu Xu, Xinkui Lin et al.
## Activation
sparse-evidence-can-suffice-agentic-evidence-seeki, 2607.18080
## References
- arXiv: https://arxiv.org/abs/2607.18080
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
This skill provides comprehensive analysis of competitor SEO and GEO strategies, revealing what's working in your market and identifying opportunities to outperform the competition.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review...
Use when an operation issue is a Paperclip cursor-window, distill, or backfill — `operationType: "distill"` or `"backfill"` and the body references a Paperclip source bundle for a project or root issue. Turn raw Paperclip activity into a wiki-insightful project page, decisions log, and history note. This skill exists specifically to replace the stiff, datestamp-heavy templated output that the deterministic distiller produces.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publi...
Semantic search, similar content discovery, and structured research using Exa API