Multifunctional Automated Novel Generation Tool Based on Large Language Models | Open Source Daily No.764
Stars: 2.2k — License: AGPL-3.0
AI_NovelGenerator is a multifunctional automatic novel generation tool based on large language models, specializing in creating multi-chapter long-form novels while maintaining plot coherence and consistent world-building.
- Novel Setting Workshop module provides world-building frameworks, character profiles, and plot blueprints
- Supports multi-stage intelligent chapter generation to ensure logical consistency and contextual continuity
- Built-in state tracking system to manage character development arcs and foreshadowing
- Vector-based semantic retrieval engine to maintain long-range contextual consistency
- Integrates with a local knowledge base for enriched and accurate references
- Automatic proofreading mechanism to detect plot contradictions and logical conflicts, improving quality
- Fully visualized end-to-end workspace via GUI for configuration, generation, and proofreading in one place
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Stars: 973 — License: NOASSERTION
HeyGenClone is a simple and open-source analogue of the HeyGen system.
- Supports multilingual video translation
- Provides voice-over and lip-sync functionality
- Uses advanced face detection and reidentification technology
- Includes video scene detection and transcription capabilities
- Allows users to customize configurations to meet specific needs
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Stars: 945 — License: MIT
VideoComposer is a controllable video diffusion model that allows flexible control over both spatial and temporal patterns in video synthesis.
- Supports control through text descriptions, sketch sequences, reference videos, or manual motions
- Provides a high-quality I2VGen-XL model for generating watermark-free 8-second videos
- Includes a Gradio UI for user-friendly interaction and experimentation
- Open-source code and pre-trained models are available for download
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Stars: 906 — License: NOASSERTION
InternLM-techreport is a multilingual large language model jointly developed by Shanghai Artificial Intelligence Laboratory and SenseTime.
- Features 104 billion parameters, pretrained on a large-scale corpus of 1.6 trillion tokens
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These projects highlight the breadth of innovation emerging from open-source AI development, from narrative generation to controllable video synthesis and advanced multilingual language modeling. For creators looking to leverage such AI tools to produce and monetize content efficiently across multiple platforms, AiToEarn offers an integrated open-source solution. It connects AI content generation with cross-platform publishing, analytics, and model rankings — enabling simultaneous distribution to major platforms such as Douyin, Kwai, WeChat, Bilibili, Rednote, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, and X (Twitter). You can explore more via the AiToEarn documentation or visit the AiToEarn blog for implementation insights.
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Uses a multi-stage progressive process for training, with fine-tuning based on human preferences.
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Demonstrates outstanding performance in multiple domains such as knowledge understanding, reading comprehension, mathematics, and programming, reaching state-of-the-art levels.
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Achieves excellent results in comprehensive examinations (such as MMLU, AGIEval, C-Eval, and Gaokao benchmarks) without relying on external tools.
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Particularly proficient in Chinese language and culture, providing a strong foundation model for Chinese applications.
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leesh3288/CVE-2023-4911 https://github.com/leesh3288/CVE-2023-4911
Stars: 388 License: NOASSERTION
CVE-2023-4911 is a proof-of-concept (PoC) project targeting a vulnerability in the `parse_tunables()` function for parsing the `GLIBC_TUNABLES` environment variable in the glibc dynamic loader.
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Vulnerability ID: CVE-2023-4911, alias “Looney Tunables.”
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Exploits a flaw in the glibc dynamic loader when handling environment variables.
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Code has been tested successfully on Ubuntu 22.04.3 and glibc version 2.35.
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The project has not been broadly adapted and is intended to verify in specific environments only.
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When working with such vulnerabilities or advanced AI models, creators and security researchers increasingly seek efficient ways to publish and monetize their findings across multiple platforms. Open-source tools like AiToEarn官网 make this easier by enabling AI-powered content generation, unified cross-platform publishing (including Douyin, Kwai, WeChat, Bilibili, Rednote, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, and X/Twitter), analytics, and AI model ranking—all in one workflow. This integration helps maximize both reach and creative impact.
