9 articles tagged with "LLMs"
The Xpertbench framework aims to enhance the evaluation of Large Language Models (LLMs) by addressing their performance plateau on traditional benchmarks through rubrics-based methods.
A recent study published on ArXiv investigates the influence of emotional signals on the behavior of large language models (LLMs), highlighting parallels with human cognition.
A new framework addresses the reliability challenges of tool-integrated LLMs, focusing on improving accuracy in real-world applications through community collaboration.
A recent study investigates the role of large language models (LLMs) in automated essay scoring, revealing uncertainties in their alignment with human grading standards.
Recent findings indicate that PLDR-LLMs pretrained at self-organized criticality exhibit reasoning abilities akin to second-order logic, with potential implications for AI systems.
A novel framework aims to enhance reasoning capabilities in Large Language Models (LLMs) while addressing computational efficiency and exploration depth trade-offs.
A recent paper published on arXiv delves into the Query-Key-Value mechanisms in language models, emphasizing their syntactic and part-of-speech implications.
A new study published on ArXiv examines the complexities of agentic task synthesis in large language models (LLMs) and their generalization capabilities under varying conditions.
A recent dataset published on ArXiv seeks to improve the instruction hierarchy in large language models, offering a structured approach to resolve conflicts in prioritization.