6 citations · 7 across the 13 of their papers we have counts for
6 papers · 1 filter
Multi-turn Training with Basic Human Feedback Helps Little on LLM Reasoning
Qiang Liu, Wuganjing Song, Zhenzhou Lin +4
The reasoning capabilities of Large Language Models (LLMs) are typically developed through the single-turn reinforcement learning, whereas real-world applications often involve mul…
UPRPRC: Unified Pipeline for Reproducing Parallel Resources -- Corpus from the United Nations
Qiuyang Lu, Fangjian Shen, Zhengkai Tang +4
The quality and accessibility of multilingual datasets are crucial for advancing machine translation. However, previous corpora built from United Nations documents have suffered fr…
SWE-Dev: Evaluating and Training Autonomous Feature-Driven Software Development
Yaxin Du, Yuzhu Cai, Yifan Zhou +6
Large Language Models (LLMs) have shown strong capability in diverse software engineering tasks. However, feature-driven development, a highly prevalent real-world task that involv…
Multi-agent Application System in Office Collaboration Scenarios
Songtao Sun, Jingyi Li, Yuanfei Dong +4
This paper introduces a multi-agent application system designed to enhance office collaboration efficiency and work quality. The system integrates artificial intelligence, machine…
AATS: Retrieval-Based KV Cache Reduction via Windowed Rotary Position Embedding and Query-Aware Vector Quantization
Junhui He, Junna Xing, Nan Wang +6
Long context large language models (LLMs) pose significant challenges for efficient serving due to the large memory footprint and high access overhead of KV cache. Retrieval-based…
PIPA: Preference Alignment as Prior-Informed Statistical Estimation
Junbo Li, Zhangyang Wang, Qiang Liu
Offline preference alignment for language models such as Direct Preference Optimization (DPO) is favored for its effectiveness and simplicity, eliminating the need for costly reinf…