3 papers
cs.AI2026
CVeDRL: An Efficient Code Verifier via Difficulty-aware Reinforcement Learning
Ji Shi, Peiming Guo, Meishan Zhang +4
Code verifiers play a critical role in post-verification for LLM-based code generation, yet existing supervised fine-tuning methods suffer from data scarcity, high failure rates, a…
cs.AI2025
AgentInit: Initializing LLM-based Multi-Agent Systems via Diversity and Expertise Orchestration for Effective and Efficient Collaboration
Chunhao Tian, Yutong Wang, Xuebo Liu +4
Proper initialization is crucial for any system, particularly in multi-agent systems (MAS), where it plays a pivotal role in determining both the system's efficiency and effectiven…
cs.LG2025
Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis
Jiaqi Zhao, Ming Wang, Miao Zhang +5
Post-training Quantization (PTQ) technique has been extensively adopted for large language models (LLMs) compression owing to its efficiency and low resource requirement. However,…