arXiv AI
Jun 9
ViMax: Agentic Video Generation
arXiv:2606. 07649v1 Announce Type: cross Abstract: Long-form video generation requires systematic narrative planning and visual consistency that current short-clip methods cannot provide.
What Gets Lost When Memory Becomes Media? Evaluating AI-Generated Oral History Visualization
arXiv:2607. 24756v1 Announce Type: cross Abstract: What gets lost when memory becomes media?
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Hugging Face Trending Papers
Aug 24
SEAM: Shot Entity-Attribute Memory for Consistent Short-Drama Generation at Scale
Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity has become a critical bottleneck. Current agent fra...
arXiv AI
Aug 25
SEAM: Shot Entity-Attribute Memory for Consistent Short-Drama Generation at Scale
arXiv:2608.22725v1 Announce Type: new Abstract: Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity ha...
arXiv AI
2d ago
DSV-Mem: Evaluating Multimodal Memory in Professional Workflows for MLLM Agents
arXiv:2610.08102v1 Announce Type: new Abstract: Conversational MLLM agents are increasingly expected to assist in professional workflows, from AI research and engineering design to product management...
arXiv AI
Jul 21
When Cultures Move: Measuring and Improving Multicultural Text-to-Video Generation
arXiv:2605. 16716v5 Announce Type: replace-cross Abstract: Text-to-video (T2V) generation has rapidly progressed in visual fidelity, yet its ability to faithfully represent multiple cultures within a single prompt remains underexplored.
arXiv AI
Jun 6
MAVEN A Multi-Agent Framework for Multicultural Text-to-Video Generation
arXiv:2605. 16716v4 Announce Type: replace-cross Abstract: Text-to-video (T2V) generation has rapidly progressed in visual fidelity, yet its ability to faithfully represent multiple cultures within a single prompt remains underexplored.
arXiv Computer Vision
Oct 2
DramaAgent: Agentic Storytelling Video Generation
arXiv:2610.00097v1 Announce Type: new Abstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with con...
Hugging Face Trending Papers
Aug 11
Order Matters: LVLMs as Judges for Temporal Reasoning in Image Sequences
As generative multimedia evolves from static image synthesis to complex, interleaved visual narratives, a foundational bottleneck has emerged: the judgment crisis. While human perception naturally synthesizes the temporal and logical flow of a story, automated evaluation systems remain largely "blind" to sequential continuity, often failing to distinguish between a coherent narrative and a semantically shuffled or contradictory sequence.
arXiv AI
Jul 9
Making Implicit Preservation Intent Explicit in Conversational Image Editing
arXiv:2607. 07051v1 Announce Type: cross Abstract: Conversational image editing requires preserving not only visible content, but also content that temporarily disappears across turns.
arXiv AI
Sep 1
CineForge: Self-Improving Agents for Long-Horizon Video Generation
arXiv:2608.29621v1 Announce Type: cross Abstract: Long-horizon story-driven video generation requires a production agent to coordinate narrative decomposition, state tracking, shot design, prompt con...
arXiv AI
Aug 10
DATAREEL: Automated Data-Driven Video Story Generation with Animations
arXiv:2604. 25220v2 Announce Type: replace Abstract: Data videos combine animated visualizations with synchronized narration to communicate quantitative information and are widely used in journalism, education, and public communication.
arXiv AI
Sep 17
MIRAGE: How Conversation State Shapes Historical Evidence Use in Multimodal Personal Agents
MIRAGE is a controlled study that examines how multimodal personal agents use historical evidence when conversation state changes. The study keeps evidence, questions, and scoring constant while varying only the conversation state, then checks if agents can determine answerability, recover the correct source, and answer from it. Results across seven multimodal backbones show distinct failure regimes before and after compaction, heavy reliance on context continuity by open-weight models, and mixed effects of retrieval pressure on source attribution.