← Search

Lin Yuan

6 accepted papers

2026

Thinker: Training LLMs in Hierarchical Thinking for Deep Search via Multi-Turn Interaction

AAAI 2026technical

Efficient retrieval of external knowledge bases and web pages is crucial for enhancing the reasoning abilities of LLMs. Previous works on training LLMs to leverage external retrievers for solving complex problems have predominantly employed end-to-end reinforcement learning. However, these approache

Cited by 0SourcePDFScholar
2025

Crafting Customisable Characters with LLMs: A Persona-Driven Role-Playing Agent Framework

EMNLP 2025

Large Language Models (LLMs) demonstrate remarkable ability to comprehend instructions and generate human-like text, enabling sophisticated agent simulation beyond basic behavior replication. However, the potential for creating freely customisable characters remains underexplored. We introduce the C

2025

Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis

AAAI 2025technical

High-quality, large-scale instructions are crucial for aligning large language models (LLMs), however, there is a severe shortage of instruction in the field of natural language understanding (NLU). Previous works on constructing NLU instructions mainly focus on information extraction (IE), neglect…

Cited by 0SourcePDFScholar
2025

MLEP: Multi-granularity Local Entropy Patterns for Generalized AI-generated Image Detection

NeurIPS 2025poster

Advances in image generation technologies have raised growing concerns about their potential misuse, particularly in producing misinformation and deepfakes. This creates an urgent demand for effective methods to detect AI-generated images (AIGIs). While progress has been made, achieving reliable per…

Cited by 0SourceScholar
2024

IEPile: Unearthing Large Scale Schema-Conditioned Information Extraction Corpus

ACL 2024short

Large Language Models (LLMs) demonstrate remarkable potential across various domains; however, they exhibit a significant performance gap in Information Extraction (IE). Note that high-quality instruction data is the vital key for enhancing the specific capabilities of LLMs, while current IE dataset…

2022

MCS: An In-battle Commentary System for MOBA Games

COLING 2022main

This paper introduces a generative system for in-battle real-time commentary in mobile MOBA games. Event commentary is important for battles in MOBA games, which is applicable to a wide range of scenarios like live streaming, e-sports commentary and combat information analysis. The system takes real…

Cited by 1SourcePDFScholar