3 citations · 6 across the 5 of their papers we have counts for
5 papers
Evidence Absence Is Not Evidence Insufficiency: Diagnosing NEI Construction Artifacts in Fact Verification
Jingxi Qiu, Zeyu Han, Cheng Huang
Evidence absence is not evidence insufficiency, but fact verification benchmarks can make them observationally similar. The Not Enough Information (NEI) label is often operationali…
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
Yifan Zhang, Chen Huang, Yueke Zhang +5
Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically salient code. We present EyeMulator, a mo…
Enhancing Code LLM Training with Programmer Attention
Yifan Zhang, Chen Huang, Zachary Karas +3
Human attention provides valuable yet underexploited signals for code LLM training, offering a perspective beyond purely machine-driven attention. Despite the complexity and cost o…
Towards Understanding What Code Language Models Learned
Toufique Ahmed, Dian Yu, Chengxuan Huang +3
Pre-trained language models are effective in a variety of natural language tasks, but it has been argued their capabilities fall short of fully learning meaning or understanding la…
Pre-Training Representations of Binary Code Using Contrastive Learning
Yifan Zhang, Chen Huang, Yueke Zhang +3
Binary code analysis and comprehension is critical to applications in reverse engineering and computer security tasks where source code is not available. Unfortunately, unlike sour…