5 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
AInsteinBench: Benchmarking Coding Agents on Scientific Repositories
Titouan Duston, Shuo Xin, Yang Sun +26
We introduce AInsteinBench, a large-scale benchmark for evaluating whether large language model (LLM) agents can operate as scientific computing development agents within real rese…
Causal-Guided Detoxify Backdoor Attack of Open-Weight LoRA Models
Linzhi Chen, Yang Sun, Hongru Wei +1
Low-Rank Adaptation (LoRA) has emerged as an efficient method for fine-tuning large language models (LLMs) and is widely adopted within the open-source community. However, the dece…
Beyond Real Data: Synthetic Data through the Lens of Regularization
Amitis Shidani, Tyler Farghly, Yang Sun +2
Synthetic data can improve generalization when real data is scarce, but excessive reliance may introduce distributional mismatches that degrade performance. In this paper, we prese…
LFD: Layer Fused Decoding to Exploit External Knowledge in Retrieval-Augmented Generation
Yang Sun, Zhiyong Xie, Lixin Zou +7
Retrieval-augmented generation (RAG) incorporates external knowledge into large language models (LLMs), improving their adaptability to downstream tasks and enabling information up…
CodeContests+: High-Quality Test Case Generation for Competitive Programming
Zihan Wang, Siyao Liu, Yang Sun +2
Competitive programming, due to its high reasoning difficulty and precise correctness feedback, has become a key task for both training and evaluating the reasoning capabilities of…
Open set label noise learning with robust sample selection and margin-guided module
Yuandi Zhao, Qianxi Xia, Yang Sun +3
In recent years, the remarkable success of deep neural networks (DNNs) in computer vision is largely due to large-scale, high-quality labeled datasets. Training directly on real-wo…