5 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.CL2026
Mutual Debiasing via Dual-Seed Comparison for Probabilistic Sampling in Large Language Models
Zihao Guo, Hongtao Lv, Chaoli Zhang +4
Although Large Language Models (LLMs) demonstrate remarkable capabilities in reasoning and decision-making, high-fidelity probabilistic sampling remains a persistent challenge. Whe…
cs.AI2025
Evaluating the Logical Reasoning Abilities of Large Reasoning Models
Hanmeng Liu, Yiran Ding, Zhizhang Fu +3
Large reasoning models, often post-trained on long chain-of-thought (long CoT) data with reinforcement learning, achieve state-of-the-art performance on mathematical, coding, and d…
cs.AI2025★ 5 cited
Logical Reasoning in Large Language Models: A Survey
Hanmeng Liu, Zhizhang Fu, Mengru Ding +4
With the emergence of advanced reasoning models like OpenAI o3 and DeepSeek-R1, large language models (LLMs) have demonstrated remarkable reasoning capabilities. However, their abi…