2 citations · 3 across the 7 of their papers we have counts for
7 papers
The World Won't Stay Still: Programmable Evolution for Agent Benchmarks
Guangrui Li, Yaochen Xie, Yi Liu +11
LLM-powered tool-calling agents fulfill user requests by interacting with environments, querying data, and invoking tools in a multi-turn process. Yet, most existing benchmarks eva…
Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods
Yifan Hao, Xingyuan Pan, Hanning Zhang +3
Supervised fine-tuning (SFT) on domain-specific data is the dominant approach for adapting foundation models to specialized tasks. However, it has been observed that SFT models ten…
Daunce: Data Attribution through Uncertainty Estimation
Xingyuan Pan, Chenlu Ye, Joseph Melkonian +2
Training data attribution (TDA) methods aim to identify which training examples influence a model's predictions on specific test data most. By quantifying these influences, TDA sup…
Adapt-Pruner: Adaptive Structural Pruning for Efficient Small Language Model Training
Rui Pan, Shivanshu Shekhar, Boyao Wang +5
Small language models (SLMs) have attracted considerable attention from both academia and industry due to their broad range of applications in edge devices. To obtain SLMs with str…
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting
Rui Pan, Dylan Zhang, Hanning Zhang +6
Bilevel optimization has shown its utility across various machine learning settings, yet most algorithms in practice require second-order information, making it challenging to scal…
G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine Translation
Xingyuan Pan, Luyang Huang, Liyan Kang +3
Large Language Models (LLMs) have demonstrated remarkable abilities in general scenarios. Instruction finetuning empowers them to align with humans in various tasks. Nevertheless,…
The VolcTrans System for WMT22 Multilingual Machine Translation Task
Xian Qian, Kai Hu, Jiaqiang Wang +4
This report describes our VolcTrans system for the WMT22 shared task on large-scale multilingual machine translation. We participated in the unconstrained track which allows the us…