5 papers · 1 filter
OdysseyArena: Benchmarking Large Language Models For Long-Horizon, Active and Inductive Interactions
Hang Yan, Fangzhi Xu, Qiushi Sun +14
The rapid advancement of Large Language Models (LLMs) has catalyzed the development of autonomous agents capable of navigating complex environments. However, existing evaluations p…
MUR: Momentum Uncertainty guided Reasoning for Large Language Models
Hang Yan, Fangzhi Xu, Rongman Xu +8
Large Language Models have achieved impressive performance on reasoning-intensive tasks, yet optimizing their reasoning efficiency remains an open challenge. While Test-Time Scalin…
Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced Reasoning
Fangzhi Xu, Hang Yan, Chang Ma +6
Advancing LLM reasoning skills has captivated wide interest. However, current post-training techniques rely heavily on supervisory signals, such as outcome supervision or auxiliary…
Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models
Fangzhi Xu, Qiushi Sun, Kanzhi Cheng +3
One of the primary driving forces contributing to the superior performance of Large Language Models (LLMs) is the extensive availability of human-annotated natural language data, w…
PathReasoner: Modeling Reasoning Path with Equivalent Extension for Logical Question Answering
Fangzhi Xu, Qika Lin, Tianzhe Zhao +2
Logical reasoning task has attracted great interest since it was proposed. Faced with such a task, current competitive models, even large language models (e.g., ChatGPT and PaLM 2)…