7 papers
NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMs
Shuaidi Wang, Zhan Zhuang, Ruping Huang +1
Diffusion Large Language Models (dLLMs) have emerged as a promising non-autoregressive generative paradigm. Given the prohibitive computational cost of full fine-tuning, Parameter-…
AdaGamma: State-Dependent Discounting for Temporal Adaptation in Reinforcement Learning
Yaomin Wang, Jianting Pan, Ran Tian +4
The discount factor in reinforcement learning controls both the effective planning horizon and the strength of bootstrapping, yet most deep RL methods use a single fixed value acro…
Beyond Uniform Credit Assignment: Selective Eligibility Traces for RLVR
Chaoli Mou, Zhan Zhuang, Xinning Chen +1
Reinforcement Learning with Verifiable Rewards (RLVR) has become a key approach for improving the reasoning abilities of large language models. However, widely used critic-free alg…
HAD: Heterogeneity-Aware Distillation for Lifelong Heterogeneous Learning
Xuerui Zhang, Xuehao Wang, Zhan Zhuang +5
Lifelong learning aims to preserve knowledge acquired from previous tasks while incorporating knowledge from a sequence of new tasks. However, most prior work explores only streams…
One-Token Verification for Reasoning Correctness Estimation
Zhan Zhuang, Xiequn Wang, Zebin Chen +4
Recent breakthroughs in large language models (LLMs) have led to notable successes in complex reasoning tasks, such as mathematical problem solving. A common strategy for improving…
MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition
Hao Zhang, Zhan Zhuang, Xuehao Wang +2
Human Activity Recognition (HAR) with wearable sensors is challenged by limited interpretability, which significantly impacts cross-dataset generalization. To address this challeng…