7 papers
Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning
Zhanyue Qin, Jia Feng, Yibo Lyu +4
Code reasoning refers to the task of predicting the output of a program given its source code and specific inputs. It can measure the reasoning capability of large language models…
Beyond Confidence: The Rhythms of Reasoning in Generative Models
Deyuan Liu, Zecheng Wang, Zhanyue Qin +3
Large Language Models (LLMs) exhibit impressive capabilities yet suffer from sensitivity to slight input context variations, hampering reliability. Conventional metrics like accura…
LFTF: Locating First and Then Fine-Tuning for Mitigating Gender Bias in Large Language Models
Zhanyue Qin, Yue Ding, Deyuan Liu +7
Nowadays, Large Language Models (LLMs) have attracted widespread attention due to their powerful performance. However, due to the unavoidable exposure to socially biased data durin…
Mitigating Gender Bias in Code Large Language Models via Model Editing
Zhanyue Qin, Haochuan Wang, Zecheng Wang +6
In recent years, with the maturation of large language model (LLM) technology and the emergence of high-quality programming code datasets, researchers have become increasingly conf…
TMGBench: A Systematic Game Benchmark for Evaluating Strategic Reasoning Abilities of LLMs
Haochuan Wang, Xiachong Feng, Lei Li +4
The rapid advancement of large language models has accelerated their application in reasoning, with strategic reasoning drawing increasing attention. To evaluate the strategic reas…
UNO Arena for Evaluating Sequential Decision-Making Capability of Large Language Models
Zhanyue Qin, Haochuan Wang, Deyuan Liu +9
Sequential decision-making refers to algorithms that take into account the dynamics of the environment, where early decisions affect subsequent decisions. With large language model…
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging
Deyuan Liu, Zhanyue Qin, Hairu Wang +12
While large language models (LLMs) excel in many domains, their complexity and scale challenge deployment in resource-limited environments. Current compression techniques, such as…