Papers with o3-mini
DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models (2026.findings-acl)
Copied to clipboard
Yakun Zhu, Zhongzhen Huang, Linjie Mu, Yutong Huang, Wei Nie, Jiaji Liu, Shaoting Zhang, Pengfei Liu, Xiaofan Zhang
| Challenge: | Existing medical benchmarks for diagnostic reasoning are limited in their ability to perform complex tasks. |
| Approach: | They propose to benchmark diagnostic capabilities of large language models to assess their accuracy and generalization bottlenecks. |
| Outcome: | The proposed model achieves 45.82%, 31.09%, and 17.79% accuracy, compared to current models, o3-mini, e1 and DeepSeek-R1 . |
Stronger Universal and Transferable Attacks by Suppressing Refusals (2025.naacl-long)
Copied to clipboard
| Challenge: | Efforts have focused on aligning models to human preferences (RLHF) . yet, it is believed that such optimization-based attacks are sample-specific. |
| Approach: | They propose an algorithm to embed a "safety feature" into models to make them safe for mass deployment. |
| Outcome: | The proposed attack achieves 25% success rate against the state-of-the-art Circuit Breaker defense, compared to 2.5% by white-box GCG. |
ScholarBench: A Bilingual Benchmark for Abstraction, Comprehension, and Reasoning Evaluation in Academic Contexts (2025.findings-emnlp)
Copied to clipboard
| Challenge: | ScholarBench evaluates domain-specific knowledge of large language models (LLMs) prior benchmarks lack the scalability to handle complex academic tasks. |
| Approach: | ScholarBench evaluates the academic reasoning ability of large language models . the benchmark is constructed through a three-step process . |
| Outcome: | ScholarBench evaluates the academic reasoning ability of large language models . the benchmark comprises 5,031 examples in Korean and 5,309 examples in English . |