# Which LLM is Best for Your SDLC? *(Sponsored)* [Read the full report »](https://bit.ly/Sonar_102825CTA) [](https://bit.ly/Sonar_102825CTA) --- ## Why the Newest LLM Isn’t Always the Best Do you assume the latest LLM is automatically the best choice for coding?
LLM Evaluation
Understanding LLM Evaluation As more companies embrace the potential of artificial intelligence (AI) to power their businesses, many are adopting large language models (LLMs) to process and produce text for diverse applications. LLMs, such as OpenAI’s GPT‑4.1, Anthropic’s Claude, and open‑source models like Meta’s
AI Safety
Author Information * First Author: Jingdi Lei — PhD student at Nanyang Technological University, focusing on large language models (LLMs), particularly model reasoning, post-training, and alignment. * Corresponding Author: Soujanya Poria — Associate Professor, School of Electrical and Electronic Engineering, Nanyang Technological University. * Other Co-authors: From Walled AI Labs, Singapore’s Infocomm Media Development
LLM Evaluation
Introducing LLM-Evalkit: Streamlined Prompt Engineering If you’ve worked with Large Language Models (LLMs), you may have faced this challenge: Your team’s prompts are scattered across documents, spreadsheets, and cloud consoles, making iteration manual and inefficient. It’s often unclear which changes truly improve performance. To address this, we’
AI hallucinations
OpenAI’s new paper explains why language models hallucinate: accuracy metrics reward guessing. It proposes penalizing confident errors, rewarding uncertainty.