3 papers
cs.AI2026
RISE-RL: Rubric-Informed Selective Exploration for Open-Ended Reinforcement Learning
Jinkun Hou, Zhuo Liu, Huimin Ren +3
Aligning Large Language Models (LLMs) for open-ended tasks is challenging because responses must satisfy multidimensional criteria without following a single correct generation tra…
cs.SE2025
Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning
Zhaoyang Chu, Yao Wan, Zhikun Zhang +7
While Code Language Models (CLMs) have demonstrated superior performance in software engineering tasks such as code generation and summarization, recent empirical studies reveal a…
cs.LG2025
EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification
Lin Zhang, Wenshuo Dong, Zhuoran Zhang +5
Understanding the internal mechanisms of transformer-based language models remains challenging. Mechanistic interpretability based on circuit discovery aims to reverse engineer neu…