5 papers
Towards Compositional Generalization of LLMs via Skill Taxonomy Guided Data Synthesis
Yifan Wei, Li Du, Xiaoyan Yu +2
Large Language Models (LLMs) and agent-based systems often struggle with compositional generalization due to a data bottleneck in which complex skill combinations follow a long-tai…
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds
Aoran Chen, Yang Feng
Multi-Task Learning (MTL) seeks to boost statistical power and learning efficiency by discovering structure shared across related tasks. State-of-the-art MTL representation methods…
MoCE: Adaptive Mixture of Contextualization Experts for Byte-based Neural Machine Translation
Langlin Huang, Mengyu Bu, Yang Feng
Byte-based machine translation systems have shown significant potential in massively multilingual settings. Unicode encoding, which maps each character to specific byte(s), elimina…
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
Zhuofan Wen, Shangtong Gui, Yang Feng
Inference acceleration of large language models (LLMs) has been put forward in many application scenarios and speculative decoding has shown its advantage in addressing inference a…
Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks
Yun Qu, Boyuan Wang, Jianzhun Shao +15
The advancement of Offline Reinforcement Learning (RL) and Offline Multi-Agent Reinforcement Learning (MARL) critically depends on the availability of high-quality, pre-collected o…