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Neural Program Synthesis By Self-Learning
Yifan Xu, Lu Dai, Udaikaran Singh +2
Neural inductive program synthesis is a task generating instructions that can produce desired outputs from given inputs. In this paper, we focus on the generation of a chunk of ass…
Unaligned Image-to-Sequence Transformation with Loop Consistency
Siyang Wang, Justin Lazarow, Kwonjoon Lee +1
We tackle the problem of modeling sequential visual phenomena. Given examples of a phenomena that can be divided into discrete time steps, we aim to take an input from any such tim…
Rethinking Exposure Bias In Language Modeling
Yifan Xu, Kening Zhang, Haoyu Dong +3
Exposure bias describes the phenomenon that a language model trained under the teacher forcing schema may perform poorly at the inference stage when its predictions are conditioned…
Learning Instance Occlusion for Panoptic Segmentation
Justin Lazarow, Kwonjoon Lee, Kunyu Shi +1
Panoptic segmentation requires segments of both "things" (countable object instances) and "stuff" (uncountable and amorphous regions) within a single output. A common approach invo…