2 citations · 3 across the 15 of their papers we have counts for
6 papers · 2 filters
Cube Bench: A Benchmark for Spatial Visual Reasoning in MLLMs
Dhruv Anand, Ehsan Shareghi
We introduce Cube Bench, a Rubik's-cube benchmark for evaluating spatial and sequential reasoning in multimodal large language models (MLLMs). The benchmark decomposes performance…
Towards Inference-time Scaling for Continuous Space Reasoning
Minghan Wang, Thuy-Trang Vu, Ehsan Shareghi +1
Inference-time scaling through multiple sample generation in combination with Process- or Outcome-Reward Model (PRM or ORM) re-ranking has proven effective for text-based reasoning…
Logical Reasoning with Outcome Reward Models for Test-Time Scaling
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi
Logical reasoning is a critical benchmark for evaluating the capabilities of large language models (LLMs), as it reflects their ability to derive valid conclusions from given premi…
TRIDENT: Benchmarking LLM Safety in Finance, Medicine, and Law
Zheng Hui, Yijiang River Dong, Ehsan Shareghi +1
As large language models (LLMs) are increasingly deployed in high-risk domains such as law, finance, and medicine, systematically evaluating their domain-specific safety and compli…
VerifiAgent: a Unified Verification Agent in Language Model Reasoning
Jiuzhou Han, Wray Buntine, Ehsan Shareghi
Large language models demonstrate remarkable reasoning capabilities but often produce unreliable or incorrect responses. Existing verification methods are typically model-specific…
Assessing the Sensitivity and Alignment of FOL Closeness Metrics
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi
The recent successful paradigm of solving logical reasoning problems with tool-augmented large language models (LLMs) leverages translation of natural language (NL) statements into…