173 citations · 2k across the 156 of their papers we have counts for
17 papers · 1 filter
On Regularization and Inference with Label Constraints
Kaifu Wang, Hangfeng He, Tin D. Nguyen +2
Prior knowledge and symbolic rules in machine learning are often expressed in the form of label constraints, especially in structured prediction problems. In this work, we compare…
On Learning Latent Models with Multi-Instance Weak Supervision
Kaifu Wang, Efthymia Tsamoura, Dan Roth
We consider a weakly supervised learning scenario where the supervision signal is generated by a transition function of labels associated with multiple input instances. We form…
GLUECons: A Generic Benchmark for Learning Under Constraints
Hossein Rajaby Faghihi, Aliakbar Nafar, Chen Zheng +7
Recent research has shown that integrating domain knowledge into deep learning architectures is effective -- it helps reduce the amount of required data, improves the accuracy of t…
ReCode: Robustness Evaluation of Code Generation Models
Shiqi Wang, Zheng Li, Haifeng Qian +11
Code generation models have achieved impressive performance. However, they tend to be brittle as slight edits to a prompt could lead to very different generations; these robustness…
Multi-lingual Evaluation of Code Generation Models
Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang +22
We present new benchmarks on evaluation code generation models: MBXP and Multilingual HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are generated…
Understanding Robust Generalization in Learning Regular Languages
Soham Dan, Osbert Bastani, Dan Roth
A key feature of human intelligence is the ability to generalize beyond the training distribution, for instance, parsing longer sentences than seen in the past. Currently, deep neu…