23 citations · 28 across the 9 of their papers we have counts for
5 papers · 1 filter
Code2Math: Can Your Code Agent Evolve Math Problems Through Exploration?
Dadi Guo, Yuejin Xie, Qingyu Liu +11
As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality problems has become a significa…
MATP-BENCH: Can MLLM Be a Good Automated Theorem Prover for Multimodal Problems?
Zhitao He, Zongwei Lyu, Dazhong Chen +2
Numerous theorems, such as those in geometry, are often presented in multimodal forms (e.g., diagrams). Humans benefit from visual reasoning in such settings, using diagrams to gai…
AIDBench: A benchmark for evaluating the authorship identification capability of large language models
Zichen Wen, Dadi Guo, Huishuai Zhang
As large language models (LLMs) rapidly advance and integrate into daily life, the privacy risks they pose are attracting increasing attention. We focus on a specific privacy risk…
PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models
Haoran Li, Dadi Guo, Donghao Li +7
The rapid development of language models (LMs) brings unprecedented accessibility and usage for both models and users. On the one hand, powerful LMs achieve state-of-the-art perfor…
Multi-step Jailbreaking Privacy Attacks on ChatGPT
Haoran Li, Dadi Guo, Wei Fan +4
With the rapid progress of large language models (LLMs), many downstream NLP tasks can be well solved given appropriate prompts. Though model developers and researchers work hard o…