9 papers
Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics
Arshia Soltani Moakhar, Iman Gholami, Max Springer +2
While Large Language Models (LLMs) have demonstrated exceptional capabilities in mathematical reasoning, they frequently produce subtle errors that evade human detection. Formal ma…
Your LLM Agents are Temporally Blind: The Misalignment Between Tool Use Decisions and Human Time Perception
Yize Cheng, Arshia Soltani Moakhar, Chenrui Fan +5
Large language model (LLM) agents are increasingly used to interact with and execute tasks in dynamic environments. However, a critical yet overlooked limitation of these agents is…
Active Learning for Decision Trees with Provable Guarantees
Arshia Soltani Moakhar, Tanapoom Laoaron, Faraz Ghahremani +2
This paper advances the theoretical understanding of active learning label complexity for decision trees as binary classifiers. We make two main contributions. First, we provide th…
GHOST: Hallucination-Inducing Image Generation for Multimodal LLMs
Aryan Yazdan Parast, Parsa Hosseini, Hesam Asadollahzadeh +4
Object hallucination in Multimodal Large Language Models (MLLMs) is a persistent failure mode that causes the model to perceive objects absent in the image. This weakness of MLLMs…
Failing to Explore: Language Models on Interactive Tasks
Mahdi JafariRaviz, Keivan Rezaei, Arshia Soltani Moakhar +3
We evaluate language models on their ability to explore interactive environments under a limited interaction budget. We introduce three parametric tasks with controllable explorati…
Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation
Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam +42
The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While mu…