Xiao Liang

Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers

2024

Although dominant in natural language processing, transformer-based models still struggle with long-sequence processing, due to the computational costs of their self-attention operations, which increase exponentially as the length of the input sequence grows.To address this …

Data Augmentation for Technical Standard Relation Extraction

2024

The paper introduces a method for fine-grained relation extraction in grid technology standards, addressing challenges in manual annotation due to complex guidelines and large-scale dataset requirements. Data augmentation techniques, specifically word-level perturbation and sentence template …

Research on RAG-Based Cognitive Large Language Model Training Method for Power Standard Knowledge

2025 · HighTech and Innovation Journal

Electrical standards encompass complex technical requirements across multiple disciplines, making their management and application a significant challenge that urgently requires efficient solutions. This paper proposes a knowledge graph retrieval-enhanced training method for large language models …

Beyond Pass@1: Self-Play with Variational Problem Synthesis Sustains RLVR

2025 · arXiv (Cornell University)

Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a key paradigm for post-training Large Language Models (LLMs), particularly for complex reasoning tasks. However, vanilla RLVR training has been shown to improve Pass@1 performance …

Chinese Knowledge Base Question Answering by Attention-Based Multi-Granularity Model

2018 · Information

Chinese knowledge base question answering (KBQA) is designed to answer the questions with the facts contained in a knowledge base. This task can be divided into two subtasks: topic entity extraction and relation selection. During …