5 papers
Contextual Biasing for LLM-Based ASR with Hotword Retrieval and Reinforcement Learning
YuXiang Kong, JunFeng Hou, Jian Tang +3
Large language model (LLM)-based automatic speech recognition (ASR) has recently achieved strong performance across diverse tasks, yet contextual biasing for named entities and hot…
Efficient Regression-Based Training of Normalizing Flows for Boltzmann Generators
Danyal Rehman, Oscar Davis, Jiarui Lu +5
Simulation-free training frameworks have been at the forefront of the generative modelling revolution in continuous spaces, leading to large-scale diffusion and flow matching model…
Self-Evolving Curriculum for LLM Reasoning
Xiaoyin Chen, Jiarui Lu, Minsu Kim +6
Reinforcement learning (RL) has proven effective for fine-tuning large language models (LLMs), significantly enhancing their reasoning abilities in domains such as mathematics and…
AOT*: Efficient Synthesis Planning via LLM-Empowered AND-OR Tree Search
Xiaozhuang Song, Xuanhao Pan, Xinjian Zhao +4
Retrosynthesis planning enables the discovery of viable synthetic routes for target molecules, playing a crucial role in domains like drug discovery and materials design. Multi-ste…
Hierarchical Contextual Manifold Alignment for Structuring Latent Representations in Large Language Models
Meiquan Dong, Haoran Liu, Yan Huang +3
The organization of latent token representations plays a crucial role in determining the stability, generalization, and contextual consistency of language models, yet conventional…