7 citations · 16 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Logic Agent: Enhancing Validity with Logic Rule Invocation
Hanmeng Liu, Zhiyang Teng, Chaoli Zhang +1
Chain-of-Thought (CoT) prompting has emerged as a pivotal technique for augmenting the inferential capabilities of language models during reasoning tasks. Despite its advancements,…
Bringing Generative AI to Adaptive Learning in Education
Hang Li, Tianlong Xu, Chaoli Zhang +6
The recent surge in generative AI technologies, such as large language models and diffusion models, has boosted the development of AI applications in various domains, including sci…
LogiCoT: Logical Chain-of-Thought Instruction-Tuning
Hanmeng Liu, Zhiyang Teng, Leyang Cui +3
Generative Pre-trained Transformer 4 (GPT-4) demonstrates impressive chain-of-thought reasoning ability. Recent work on self-instruction tuning, such as Alpaca, has focused on enha…