No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by azminewasi · Agent Tool · ★ 72
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Awesome ICLR 2024 LLM Papers Collection This repo contains a comprehensive compilation of LLM papers that were presented at the esteemed International Conference on Learning Representations (ICLR) in the year 2024. 2023-2024 will be full of LLMs and 311 papers shows the evidence. Click to read full abstract and get openreview URL. Detecting Pretraining Data from Large Language Models This paper addresses the challenge of detecting data used to train large language models (LLMs) by proposing a novel method called MIN-K PROB. Unlike existing methods that rely on training a reference model, MIN-K PROB identifies pretraining data based on the assumption that unseen examples contain outlier words with low probabilities under the LLM. Details Abstract: Although large language models (LLMs) are widely deployed, the data used to train them is rarely disclosed. Given the incredible scale of this data, up to trillions of tokens, it is all but certain that it includes potentially problematic text such as copyrighted materials, personally identifiable information, and test data for widely reported reference benchmarks.
| Stars | 72 |
| Forks | 5 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 48.5390774540323/100 |
| Last Updated | 2024-04-04 |
| Created | 2024-03-18 |
| Est. Tokens | ~64k |
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Awesome-LLMs-ICLR-24 is It is a comprehensive resource hub compiling all LLM papers accepted at the International Conference on Learning Representations (ICLR) in 2024.. It is categorized as a Agent Tool with 72 GitHub stars.
You can find installation instructions and usage details in the Awesome-LLMs-ICLR-24 GitHub repository at github.com/azminewasi/Awesome-LLMs-ICLR-24. The project has 72 stars and 5 forks, indicating an active community.
Awesome-LLMs-ICLR-24 is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Awesome-LLMs-ICLR-24 on Agent Skills Hub include SecGPT, promptdesk, palico-ai. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.