Investigating the Role of Prompting and External Tools in Hallucination Rates of LLMs

🤖 Marco-o1: Towards Open Reasoning Models for Open-Ended SolutionsThe Alibaba MarcoPolo team presents Marco-o1, a large reasoning model designed to excel in open-ended problem-solving. Building upon ...

23 Marras 202414min

⚖️ Scaling Laws for PrecisionThis research paper investigates the impact of precision in training and inference on the performance of large language models. The authors explore how precision affects t...

18 Marras 202418min

⌛️ The Surprising Effectiveness of Test-Time Training for Abstract ReasoningThis paper examines how test-time training (TTT) can enhance the abstract reasoning abilities of large language models (LLMs...

14 Marras 202414min

🔷 Qwen2.5-Coder Technical ReportThe report introduces the Qwen2.5-Coder series, which includes the Qwen2.5-Coder-1.5B and Qwen2.5-Coder-7B models. These models are specifically designed for coding ta...

12 Marras 202424min

😈 Attacking Vision-Language Computer Agents via Pop-upsThis research paper examines vulnerabilities in vision-language models (VLMs) that power autonomous agents performing computer tasks. The author...

9 Marras 202421min

📓 Number Cookbook: Number Understanding of Language Models and How to Improve ItThis research paper examines the numerical understanding and processing abilities (NUPA) of large language models (LLMs...

8 Marras 202416min

🧩 Jigsaw Puzzles: Splitting Harmful Questions to Jailbreak Large Language ModelsThis research paper investigates the vulnerabilities of large language models (LLMs) to "jailbreak" attacks, where mali...

7 Marras 202416min

🤝 Multi-expert Prompting with LLMsThe research paper presents Multi-expert Prompting, a novel method for improving the reliability, safety, and usefulness of Large Language Models (LLMs). Multi-exper...

5 Marras 202412min