1 citations · 1 across the 5 of their papers we have counts for
5 papers
pCTFusion: Point Convolution-Transformer Fusion with Semantic Aware Loss for Outdoor LiDAR Point Cloud Segmentation
Abhishek Kuriyal, Vaibhav Kumar, Bharat Lohani
LiDAR-generated point clouds are crucial for perceiving outdoor environments. The segmentation of point clouds is also essential for many applications. Previous research has focuse…
Controlled Text Generation with Hidden Representation Transformations
Vaibhav Kumar, Hana Koorehdavoudi, Masud Moshtaghi +3
We propose CHRT (Control Hidden Representation Transformation) - a controlled language generation framework that steers large language models to generate text pertaining to certain…
Identifying and Mitigating Gender Bias in Hyperbolic Word Embeddings
Vaibhav Kumar, Tenzin Singhay Bhotia, Tanmoy Chakraborty
Euclidean word embedding models such as GloVe and Word2Vec have been shown to reflect human-like gender biases. In this paper, we extend the study of gender bias to the recently po…
Fair Embedding Engine: A Library for Analyzing and Mitigating Gender Bias in Word Embeddings
Vaibhav Kumar, Tenzin Singhay Bhotia
Non-contextual word embedding models have been shown to inherit human-like stereotypical biases of gender, race and religion from the training corpora. To counter this issue, a lar…
Nurse is Closer to Woman than Surgeon? Mitigating Gender-Biased Proximities in Word Embeddings
Vaibhav Kumar, Tenzin Singhay Bhotia, Tanmoy Chakraborty
Word embeddings are the standard model for semantic and syntactic representations of words. Unfortunately, these models have been shown to exhibit undesirable word associations res…