3 papers
cs.AI2026
LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
Kaijian Zou, Aaron Xiong, Yunxiang Zhang +6
Competitive programming problems are increasingly used to evaluate the coding capabilities of large language models (LLMs) due to their complexity and ease of verification. Yet, cu…
cs.CL2026
The Wrong Kind of Right: Quantifying and Localizing Misfired Alignment in LLMs
Naihao Deng, Yiming Feng, Chimaobi Okite +4
Warning: This paper studies stereotypes and biases, and contains potentially disturbing examples, used for illustration purposes only. Our findings should not be interpreted as an…
cs.CL2025
On Many-Shot In-Context Learning for Long-Context Evaluation
Kaijian Zou, Muhammad Khalifa, Lu Wang
Many-shot in-context learning (ICL) has emerged as a unique setup to both utilize and test the ability of large language models to handle long context. This paper delves into long-…