6 citations · 15 across the 8 of their papers we have counts for
5 papers · 1 filter
Editing Common Sense in Transformers
Anshita Gupta, Debanjan Mondal, Akshay Krishna Sheshadri +4
Editing model parameters directly in Transformers makes updating open-source transformer-based models possible without re-training (Meng et al., 2023). However, these editing metho…
ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution
Ankita Gupta, Marzena Karpinska, Wenlong Zhao +5
Large-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been c…
IGA : An Intent-Guided Authoring Assistant
Simeng Sun, Wenlong Zhao, Varun Manjunatha +5
While large-scale pretrained language models have significantly improved writing assistance functionalities such as autocomplete, more complex and controllable writing assistants h…
Compressing Transformer-Based Semantic Parsing Models using Compositional Code Embeddings
Prafull Prakash, Saurabh Kumar Shashidhar, Wenlong Zhao +3
The current state-of-the-art task-oriented semantic parsing models use BERT or RoBERTa as pretrained encoders; these models have huge memory footprints. This poses a challenge to t…
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…