1 citations · 1 across the 6 of their papers we have counts for
6 papers
FieldGen: From Teleoperated Pre-Manipulation Trajectories to Field-Guided Data Generation
Wenhao Wang, Kehe Ye, Xinyu Zhou +9
Large-scale and diverse datasets are vital for training robust robotic manipulation policies, yet existing data collection methods struggle to balance scale, diversity, and quality…
Revealing and Mitigating Over-Attention in Knowledge Editing
Pinzheng Wang, Zecheng Tang, Keyan Zhou +3
Large Language Models have demonstrated superior performance across a wide range of tasks, but they still exhibit undesirable errors due to incorrect knowledge learned from the tra…
LOGO -- Long cOntext aliGnment via efficient preference Optimization
Zecheng Tang, Zechen Sun, Juntao Li +2
Long-context models(LCMs) have shown great potential in processing long input sequences(even more than 100M tokens) conveniently and effectively. With significant progress, recent…
Unleashing LLM Reasoning Capability via Scalable Question Synthesis from Scratch
Yuyang Ding, Xinyu Shi, Xiaobo Liang +4
Improving the mathematical reasoning capabilities of Large Language Models (LLMs) is critical for advancing artificial intelligence. However, access to extensive, diverse, and high…
OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning
Dan Qiao, Yi Su, Pinzheng Wang +18
Large Language Models (LLMs) have played an important role in many fields due to their powerful capabilities.However, their massive number of parameters leads to high deployment re…
OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch
Juntao Li, Zecheng Tang, Yuyang Ding +9
Large language models (LLMs) with billions of parameters have demonstrated outstanding performance on various natural language processing tasks. This report presents OpenBA, an ope…